AI Researcher jobs in Israel

Job Description We are seeking a highly accomplished AI Researcher to be part of the development of next-generation Foundation Models and Generative AI systems. In this role, you will bridge the gap between cutting-edge academic research and production-grade AI infrastructure. You will build, design, and fine-tune large-scale architectures (including LLMs, Multimodal, and Tabular Foundation Models) while applying them to complex, real-world domains like agentic behavior, coding and decision making. In your day-to-day, you will: • Conduct pioneering research in deep learning and generative AI, specializing in Foundation Models, NLP, alignment, and multimodal learning • Deal with the impact of the models on production traffic, cost quality and latency • Train and scale state-of-the-art architectures using techniques like Post-Training SFT, Knowledge Distillation, LoRA, and sparse/hybrid model architectures • Own the AI lifecycle—from algorithmic prototyping and synthetic data generation to deploying production-grade AI features in fast-paced or big-data environments • Drive research initiatives, author publications/patents, and collaborate with other research teams to integrate intelligent capabilities into core products Qualifications • 5+ years of experience as a Research Scientist or Algorithm Developer within world-class AI labs or high-growth GenAI startups • Ph.D. or Master’s degree with honors in computer science, data science, statistics, or a highly quantitative field from a top-tier institution • Expert-level proficiency in PyTorch and deep learning training/inference optimization • Hands-on experience training, fine-tuning, or optimizing large-scale LLMs in research or production environments • Advanced programming skills in Python and/or C/C++ with experience in production-grade code and big data infrastructure • A portfolio of peer-reviewed publications in top-tier AI/ML venues or granted patents in advanced machine learning systems Additional Information We're Base44, a newly acquired part of Wix, on a mission to redefine how software is built. Our AI-powered platform enables anyone to create custom software applications using natural language—no coding required. Operating like a startup within Wix, we're fast, collaborative, and focused on solving complex problems with simple, powerful solutions. We exist to empower creators, solo founders, startups, entrepreneurs, and side hustlers to bring their ideas to life. Whether you're launching a product, validating a concept, or exploring a new idea, Base44 is here to help you build it. We're growing rapidly, the potential is immense, and with your expertise, we can drive user-driven growth to new heights.

About Us Novee is the AI penetration testing platform built for a world where attackers operate at machine speed. Our AI agents think like real attackers, continuously finding and validating exploitable risk so security teams can fix what matters first. We raised $51.5M in four months, backed by top investors YL Ventures, Canaan Partners, and Oren Zeev - one of the fastest funding trajectories in offensive security. Our proprietary AI models outperforms frontier LLMs on real exploitation benchmarks, and we're just getting started. We're a global team with offices in Tel Aviv, the US and the UK, founded by offensive security experts. We work with hundreds of global enterprises to help them secure their environments and innovate faster. We're at the cutting edge of AI and cyber. We move fast, work with the best, and have fun together. About the Role We're looking for an AI Researcher to join our model training team, which designs, trains and evaluates the language models powering Novee's autonomous pentesting agents. This role is a unique opportunity to help push the frontier of AI capabilities in cybersecurity. Reporting to our Head of AI and working alongside exceptional researchers, you will develop and apply cutting-edge reinforcement learning methods to shape the behavior of our models in dynamic, long-horizon environments. You'll own the full research lifecycle: Defining hypotheses, designing experiments, training models, analyzing results and iterating. You'll work across the full post-training stack, including data pipelines, verifiers, reinforcement learning algorithms and evaluations. This role combines deep research with hands-on engineering, and has a direct impact on the quality of our product. Responsibilities Research, train, and evaluate language models for cybersecurity tasks. Devise evaluations that capture what matters. Make sure the numbers are meaningful and make the numbers go up. Analyze errors and failure modes. Develop post-training recipes to improve model reasoning, tool use, exploration and decision-making in challenging offensive security tasks. Develop large scale data pipelines, complex RL environments, reliable verification methods and effective reinforcement learning algorithms. Design, run and analyze experiments to prove new methods and ship compounding improvements. Collaborate with cybersecurity researchers on training data, evaluations and reward signals. Partner with our infrastructure team to rapidly scale research efforts. Implement research ideas in Python, leveraging modern deep learning tools such as inference frameworks (vLLM, SGLang, …), training frameworks (verl, slime, …), and training APIs (Tinker and similar) in an AI-first development environment. Work with engineering teams to translate research outcomes into capabilities used by our agents. Review relevant research and assess its practical value for the problems we're solving. Requirements Master's degree with a research thesis in Computer Science / Mathematics / Physics / Engineering / another STEM field; or Bachelor's degree plus equivalent industry / army research experience. Hands-on experience in data-driven computational research: machine learning, algorithm development, numerical analysis, data science, statistical modeling or similar. Proven ability to take open-ended problems from vague ideas to working implementations. First-principles thinking and the ability to critically evaluate experimental data and distinguish real effects from noise and bugs. A strong understanding of deep learning and language models. Comfort with ambiguity and fast-paced research environments where priorities and core assumptions evolve quickly. Great communication skills and the ability to collaborate in a small, agile team. Independence, curiosity, and a deep bias for action. Nice to Have PhD in a relevant field or relevant research publications. Specific background in cybersecurity. Specific background in reinforcement learning, particularly for language models or agents. Hands-on experience with deep learning training and/or inference frameworks. Hands-on experience running and debugging large-scale distributed systems.

Twine builds AI Digital Employees who help cyber teams close the execution gap. Our first AI Digital Employee, Alex, learns, understands and takes away the burden of Identity and Access Management (IAM) tasks - proactively completing the organization's cyber objectives. About the role: You'll design, build, and ship the AI systems behind Alex: production agents that reason over customer identity data, call real tools, and complete IAM tasks end to end. Starting from a cybersecurity need, you'll frame the technical problem, choose an approach, and own the solution through production: architecture, implementation, evaluation, deployment, and iteration on real customer behavior. You'll build on Twine's shared agent infrastructure and extend it: new tools and integrations, workflow orchestration, context and memory management, evaluation harnesses, and the guardrails that keep an autonomous agent safe inside a customer's environment. This is a hands-on engineering role, not a research position. The goal is not to prove that an idea can work; it is to make it useful, reliable, and observable for customers in production. Responsibilities Design, implement, and ship AI-powered features for complex cybersecurity workflows, from prototype to production. Build the systems that make agents work in practice: tool integrations, planning and orchestration logic, context management, structured outputs, and recovery from failures. Choose the right technical approach for each problem, combining models, deterministic logic, data, and conventional software where appropriate. Define quality for each use case and build the evaluation pipelines that measure correctness, task completion, consistency, safety, latency, and cost, and wire them into CI and release. Debug agent behavior in production: trace failures to their root cause in the prompt, tool, data, or architecture, and fix it. Own the reliability, observability, and cost of the agent systems you build. Collaborate with cybersecurity experts, product, and platform engineers throughout development. Requirements Excellent software engineering skills and substantial production experience with Python. Experience shipping and operating backend systems in production: APIs, async processing, data pipelines, testing, and observability. Hands-on experience building applications on modern language models: tool use, structured generation, retrieval, prompt and context management, and evaluation. Sound judgment about when to use an AI technique and when a deterministic approach is more effective. Comfort owning a problem end to end, from an ambiguous requirement to a system running reliably in production. Nice to have Building autonomous or long-running agents that interact with real systems. Building evaluation pipelines, simulations, or benchmarks for model behavior. Experience in cybersecurity, identity, security operations, or enterprise automation. Experience with agent frameworks, MCP, or LLM observability and tracing tools. Intertwine your future with ours Applying for AI Engineer. Send us your details and CV - we read every one.

Description We are seeking a Senior AI Researcher to lead post-training evaluation, red-teaming, and reinforcement learning (RL) gym audits on open-weight models. The ideal candidate will establish rigorous benchmarking methodologies, evaluate large language models (LLMs) against complex threats like Indirect Prompt Injections (IPI), and construct post-training evaluation pipelines that accurately measure realistic frontier-level security capabilities. Key Responsibilities RL Post-Training & Benchmarking • Execute post-training runs (e.g. GRPO) using mainstream open-weight generalist models against security-focused RL environments, targeting threat vectors like Indirect Prompt Injection (IPI). • Reward Diagnostics & Trace Analysis - Analyze live loss curves and rollout traces to identify reward hacking, lazy policy convergence, and flawed or over/under-specified verifiers. Task & Environment Auditing • Review tasks and multi-turn environments (including tool use, web navigation, and computer use) for realism, threat model accuracy, data distribution, and dataset balance. Performance Reporting (Gym Cards) • Generate comprehensive evaluation cards detailing hill-climbing performance uplift across checkpoints, failure modes, tokens/turns per rollout, and task-level success rates. Integration & Orchestration • Integrate dockerized environments (e.g., Harbor format) into internal training frameworks, optimizing reset/statefulness semantics, concurrency, and throughput ceilings. Requirements Required Qualifications • Technical Background: M.S. or Ph.D. in Data Science, Machine Learning, Computer Science, or equivalent practical experience in deep learning. • RL & Post-Training Expertise: Strong hands-on experience training large-scale models using RL algorithms (e.g. GRPO, PPO) on open-weight architectures. • AI Security Expertise: Solid understanding of LLM vulnerabilities, red-teaming methodologies, and defensive alignment against IPI attacks. • Infrastructure Skills: Proficiency in PyTorch, Docker containerization, and distributed training architectures. • Diagnostic Skills: Ability to analyze agent rollout traces, craft deterministic rubrics/verifiers, and debug complex reward shaping flaws. Preferred Qualifications • Prior experience working with standard RL gym formats, such as Harbor. • Experience evaluating complex agentic workflows in tool-use or web-browser environments. • Familiarity with evaluating open-weight models similar to Llama or Mistral against adversarial workloads. About Alice Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!

Description About Slice Global Equity Slice Global Equity is redefining how companies manage equity, compliance, and tax across borders. We've raised $32M to date, including a Series A led by Insight Partners, with continued backing from TLV Partners, R-Squared Ventures, and Jibe Ventures. Slice is building an AI-native equity platform that automates global compliance in real time, across 60+ countries. We sit at the intersection of fintech, legaltech, and AI, solving one of the hardest infrastructure problems in global business. We're headquartered in New York City, with an office in Tel Aviv. We move fast, take ownership, and think AI-first. If that sounds like you, we'd love to meet you. We’re looking for an experienced, hands-on Senior AI Researcher to lead research efforts at Slice and help shape the next generation of AI capabilities across our platform. You’ll explore complex, domain-specific challenges, define research directions, and translate promising ideas into practical product capabilities. Your work will span applied research, experimentation, and model development—including building and adapting large and small language models using proprietary data, domain knowledge, and modern training techniques. You’ll work with complex financial documents, structured and unstructured financial data, and legal and compliance data and knowledge, developing approaches that help AI interpret and reason across these sources. Working closely with the CTO, engineering teams, and domain experts, you’ll have significant ownership over both the questions we investigate and the approaches we take. We’re looking for someone who combines strong research fundamentals with the drive to build, test, and bring ideas into production. What You’ll Do • Lead applied AI research efforts. Identify meaningful opportunities, shape the research roadmap, and drive initiatives from initial exploration through validation and implementation. • Build and improve models. Develop, train, and adapt models using approaches such as fine-tuning, post-training, distillation, and other relevant techniques. • Work with complex documents and data. Explore methods for understanding and reasoning over financial documents, structured business data, and legal and compliance information, in collaboration with domain experts. • Drive rigorous experimentation. Formulate hypotheses, build datasets and evaluation frameworks, and systematically measure performance, reliability, and tradeoffs. • Connect research to real-world applications. Collaborate with engineers and domain experts to turn research outcomes into scalable, production-ready capabilities. • Advance our research practices. Evaluate emerging methods, share findings, and help establish strong standards for experimentation, model development, and responsible use of data. Requirements What You’ll Bring • 6+ years of experience in AI/ML research or applied science, with a strong background in deep learning and recent hands-on experience with language models. • Proven experience building, training, or adapting models, including ownership of data preparation, experimentation, and evaluation—not just integrating third-party model APIs. • Strong proficiency in Python and modern deep learning frameworks, such as PyTorch, and familiarity with the language-model training ecosystem. • A solid understanding of model architectures, optimization, training methodologies, and evaluation.. • Strong research judgment: the ability to frame ambiguous problems, design meaningful experiments, analyze results, and make evidence-based decisions. • The ability to work independently, take technical ownership, and collaborate effectively with engineering, product, and domain experts. Nice to Have • An M.Sc. or Ph.D. in Computer Science, Machine Learning, or a related field, or an equivalent research track record. • Experience with advanced post-training methods, reinforcement learning, synthetic data, knowledge distillation, or efficient model training and inference. • Experience in document understanding, information extraction, or reasoning across structured and unstructured data, particularly in financial, legal, or compliance domains. • Research publications, meaningful open-source contributions, or a track record of bringing research into production. Why Join Slice • Build with purpose: Apply AI to solve global compliance at scale. • High ownership: Work directly on product-critical systems with real customer impact. • Technical depth: Work across architecture, UX, and infrastructure. • Collaboration: Partner with top engineers and alumni of elite technology units. • Team culture: Collaborative, ambitious, and impact-driven. • Startup energy: Join a high-growth company backed by top investors, scaling globally, and redefining fintech infrastructure.

We are making the future of Mobility come to life starting today. At Autofleet we support the world's largest vehicle fleet operators and transportation providers to optimize existing operations and seamlessly launch new, dynamic business models - driving efficient operations and maximizing utilization. We are looking for a talented AI Applied Researcher to help us develop advanced AI solutions that will empower impactful projects. The Data Science team leads the AI research and innovation efforts of the company, and is focused on pushing AI boundaries to enhance the product and optimize processes. What You’ll Do • Enterprise AI Agent Development: Designing, building, and deploying AI agents that automate and augment high-value workflows across business functions • Agentic Architecture & Orchestration: Owning the end-to-end agent stack - from tool use, memory management, and multi-step planning to human-in-the-loop escalation patterns, guardrails and audit trails. • Evaluation & Continuous Improvement: Defining agent evaluation frameworks that measure task completion, accuracy, hallucination rates, latency, and business impact - then iterating on agent behavior based on real usage data and stakeholder feedback. • Collaborate with engineering teams to design, build, and maintain production pipelines. • Stay up to date with the latest developments in AI, machine learning, and related fields, focusing on LLMs, exploring how emerging technologies can be applied to improve products and services. Requirements • Master’s/Ph.D. in Computer Science, Electrical Engineering, Machine Learning, information systems engineering, or related field. • 3+ years of applied AI/ML experience with a focus on Generative AI, LLMs, and deep learning. • Depth in agentic system design, retrieval-augmented generation, context and tool engineering, and rigorous evaluation. • Familiarity with AI frameworks (e.g., HuggingFace Transformers, LangChain, scikit-learn, PyTorch) • Familiarity with embedding models and vector databases • Exceptional problem-solving, creative thinking, and analytical skills. • Experience with voice AI technologies, speech recognition, or text-to-speech systems - strong advantage.

Description Mentee Robotics, now part of Mobileye, brings world-class robotics expertise, together with Mobileye's decades of leadership in computer vision, machine learning, and autonomous driving technologies. Building on that foundation, Mentee by Mobileye is creating the "MenteeBot", the AI-first humanoid robot that combines perception, reasoning, learning, and advanced dexterous manipulation, designed to work alongside people in their everyday lives, at the workplace and in the home. At Mobileye, our technologies power more than 230 million vehicles worldwide and have helped shape the future of autonomous mobility. With teams around the world, we continue to innovate at the forefront of autonomous systems, advancing the next generation of Physical AI for real life. Responsibilities • Design, implement, and train state-of-the-art neural network architectures for robotic applications, including large multimodal models (vision, language, sensor data) and generative models. • Architect and maintain scalable deep learning frameworks for training on massive, real-world robot datasets. • Develop and implement cutting-edge techniques in areas such as imitation learning, reinforcement learning, self-supervised learning, and video-based models. • Own the full machine learning lifecycle: define data collection and labeling strategies, build high-throughput data pipelines, and establish robust evaluation and deployment protocols. • Collaborate closely with software, hardware, and controls teams to integrate and test your models on physical robots. • Leverage and contribute to internal tooling for large-scale data processing, model experimentation, and continuous integration. Requirements • Proven experience (M.S., Ph.D., or equivalent industry experience) in Computer Science, AI, or a related field. • Strong software engineering skills are non-negotiable; demonstrated excellence in solving complex engineering problems, particularly in Python. • A deep, "under the hood" understanding of modern deep learning, including network architectures, loss functions, optimization, and transformers. • Extensive hands-on experience with PyTorch. • A proven track record of training large-scale deep learning models on large datasets. • Ability to thrive in a fast-paced, high-impact environment where solutions are often unclear and require deep exploration. Advantages • Experience with training large models (e.g., LLM, VLM, VLA). • Prior experience working with robotic learning systems. • Experience with multi-task learning, imitation learning, or reinforcement learning. • A strong publication record in top-tier AI or robotics conferences (e.g., NeurIPS, ICML, CVPR, RSS, CoRL).

About Irregular Irregular is the first frontier security lab with the mission of protecting the world in the time of increasingly capable and sophisticated AI systems. We build next-generation defenses through high-fidelity research platforms that simulate and monitor real-world AI security scenarios. As AI systems become more powerful, we focus on staying ahead of emerging threats and vulnerabilities, ensuring these transformative technologies can be deployed safely and securely. About the Role As an AI researcher at Irregular, you'll be at the forefront of researching advanced frontier model capabilities and agent behavior, and help shape the future of AI security evaluation and mitigation. In this role, you will advance the frontier knowledge of AI and agentic frameworks, methods of assessing their ability, and mitigations for dangerous capabilities. Representative projects: • Researching capability elicitation methods to enhance model performance in evaluations. • Researching methodologies to assess generalization and coverage in model capabilities evaluation frameworks. • Contributing to academic publications and delivering research findings to customers. • Creating unique solutions to mitigate scenarios of AI loss of control or misalignment. • Advising and supporting the development of the products we’re building. You may be a good fit if you: • Have a strong research experience in machine learning, particularly with frontier AI models. • Can design and implement novel research approaches for emerging AI challenges. • Work well in a multidisciplinary team and can adapt to rapidly evolving research questions. • Have a track record of publishing peer-reviewed research in top-tier venues (e.g., AAAI, ACL, EMNLP, ICLR, ICML, Nature, NeurIPS, Science, or similar). • Care about the societal impacts of your work.

Description What we are looking for: Nova is looking for a highly capable and experienced Deep Learning Researcher to lead and develop advanced deep learning solutions for metrology challenges within Nova’s CTO group. Role Responsibilities What you will be doing: • Lead feasibility studies and proof-of-concept investigations for advanced deep learning solutions addressing complex metrology challenges. • Design, develop, and evaluate deep learning infrastructure for early-stage metrology technologies. • Propose and drive new deep learning directions, research ideas, and innovative approaches in collaboration with the CTO group. • Work closely with multidisciplinary teams to translate research concepts into practical metrology solutions. • Stay up to date with state-of-the-art deep learning methods and apply them to novel semiconductor metrology problems. Requirements Requirements: • M.Sc. or Ph.D. in Data Science, Computer Science, Engineering, Physics, or a related field. • +4 years of hands-on experience in Data Science. • Strong experience with advanced deep learning algorithms and infrastructure. • High proficiency in Python with excellent coding skills. • High level of motivation and ability to work independently. • Strong collaboration skills and a proven team player. Get to know us better: Nova (NASDAQ: NVMI) is a global company and a leading provider of innovative metrology solutions for process control in semiconductor manufacturing. With a team of ~1200 people in three R&D centers and 27 field offices, we bring insights into the world’s most advanced industry. We leverage multiple technology fields such as physics, optics, chemistry, and algorithms to develop hardware and software solutions that measure almost every advanced computer chip built in the world. Nova dives deep into dimensions and layers at the atomic level to extract unique insights and provide our customers with crucial decision-making data, managing critical challenges by providing unique, differentiated solutions. Our outstanding people-focused and innovative culture means every person at Nova has the power to make an impact and significantly redefine what people can achieve through technology. Join us if you are A dreamer and brilliant high aimer who sees the impossible as the starting point and loves working in a multidisciplinary global team to create innovative breakthroughs. If you need assistance due to a disability, you may contact us at [email protected]

Description About Cyera Come join the company building the security operating model for the age of AI. AI has changed how data is used — and security must change with it. Cyera's mission is to empower businesses to accelerate AI Adoption by defining a holistic approach to securing AI - from data to access to model. Instead of perimeter controls and static policies, Cyera provides a unified control plane that understands relationships between data, access, and behaviors across humans, systems, and AI. Backed by the world’s leading investors and working with a large and growing list of Fortune 1000 companies, we are looking for world-class talent to join us as we usher in the new era of data and AI security. About the Role As an AI Researcher on Cyera’s Research group, you’ll research, develop and productionize LLMs powered applications and AI-agents. You’ll partner closely with Product and Engineering to turn open-ended data-security challenges into measurable experiments and shipped features. You’ll own the end-to-end lifecycle - from problem framing and data strategy to evaluation, deployment, and ongoing monitoring - helping customers discover, protect, and govern their data at scale. What You’ll Do • Responsible for the end-to-end research process. This includes identifying problems, preparing data, tuning and developing models, deploying to production, and analyzing outcomes. • You will be a hands-on domain leader, laying the foundations of our data science workflows and algorithms. This is an excellent opportunity to work with endless amounts of data and creatively generate insights that will increase the ability to classify tons of data. • Develop, evaluate, and maintain deep learning and NLP solutions to enhance Cyera’s core capabilities in sensitive data classification. • Design and architect production-grade agentic workflows. Establish rigorous evaluation pipelines to benchmark agent accuracy, latency, and cost, ensuring reliable, scalable solutions for real-world customer problems • Innovation and creative thinking are the keys! Implementing ML models to the entire research process - clustering, text extraction, document analysis, and tabular data classification. • Join a “full stack” AI group, including research engineering, MLEs, data operations, and security researchers. You will accelerate the path from research to production, ensuring results are both quick and precise. Requirements Who You Are Must-Haves • MSc in Computer Science, Mathematics, Statistics, Physics or a related field • 5+ years of experience as a Data Scientist/AI Researcher/NLP Researcher/Applied Scientist • Strong knowledge and understanding of machine learning concepts and techniques. • Deep understanding in modern NLP: LLMs, transformers, etc. • Proven experience in applying LLM-based applications or AI agents. • Experience in deploying and optimizing ML / LLMs / AI-agents to production processes • Experience with data pipelines / big-data analytics • Self-learner, initiator, able to quickly learn new technologies Why Join Us? At Cyera, we care about collaboration, innovation, and agility. We take “teamwork” seriously - with our inclusive and supportive culture at the forefront - and we’re just as serious about nurturing Cyerans to grow, both personally and professionally. Feel free to apply even if your experience doesn’t tick every box. We’re building something special here - and we welcome Cyerans with diverse backgrounds, perspectives, and experiences.

Description About Cyera Come join the company building the security operating model for the age of AI. AI has changed how data is used — and security must change with it. Cyera's mission is to empower businesses to accelerate AI Adoption by defining a holistic approach to securing AI - from data to access to model. Instead of perimeter controls and static policies, Cyera provides a unified control plane that understands relationships between data, access, and behaviors across humans, systems, and AI. Backed by the world’s leading investors and working with a large and growing list of Fortune 1000 companies, we are looking for world-class talent to join us as we usher in the new era of data and AI security. About the Role As an AI Research Team Lead on Cyera’s Research group, you will mentor a talented team of researchers, set the strategic vision for research initiatives, and drive team-wide project goals. You’ll partner closely with Product and Engineering leadership to turn open-ended data-security challenges into measurable experiments and shipped features. You will manage the critical balance between research exploration and product delivery, owning the end-to-end lifecycle—from problem framing and data strategy to evaluation, deployment, and ongoing monitoring—helping customers discover, protect, and govern their data at scale. What You’ll Do • Lead and mentor a team of AI researchers, fostering a culture of excellence and innovation while overseeing the end-to-end research lifecycle. • You will act as the technical and strategic lead, defining team priorities, roadmap, and data science methodologies. • Mentor and grow team members through technical guidance, career development, and peer reviews. • Collaborate with cross-functional leadership in Product and Engineering to align research efforts with core business objectives and customer needs. • Manage team performance, resource allocation, and timely project delivery within an agile environment. • Develop, evaluate, and maintain deep learning and NLP solutions to enhance Cyera’s core capabilities in sensitive data classification. • Design and architect production-grade agentic workflows. Establish rigorous evaluation pipelines to benchmark agent accuracy, latency, and cost, ensuring reliable, scalable solutions for real-world customer problems • Innovation and creative thinking are the keys! Implementing ML models to the entire research process - clustering, text extraction, document analysis, and tabular data classification. • Join a “full stack” AI group, including research engineering, MLEs, data operations, and security researchers. You will accelerate the path from research to production, ensuring results are both quick and precise. Requirements Who You Are Must-Haves • BSc in computer science, math, physics, or a related field • 7+ years of experience as an AI Researcher/NLP Researcher/Applied Scientist, including experience leading or managing research teams • Proven track record of building and managing high-performing AI research / Data Science teams. • Solid grounding in core machine and deep learning concepts and techniques, data challenges (imbalance, scaling etc.), and evaluation. • Demonstrated expertise in applying LLMs - prompt engineering and prompt tuning (few-shot, chain-of-thought, tool/function calling, routing), task adaptation (instruction/SFT, PEFT/LoRA, DPO/RLHF), retrieval-augmented generation, rigorous evaluation and production deployment with appropriate safety, latency, and cost controls. • Self-learner, initiator, able to quickly learn new technologies • Experience in NLP - a significant advantage Why Join Us? At Cyera, we care about collaboration, innovation, and agility. We take “teamwork” seriously—with our inclusive and supportive culture at the forefront—and we’re just as serious about nurturing Cyerans to grow, both personally and professionally. Feel free to apply even if your experience doesn’t tick every box. We’re building something special here—and we welcome Cyerans with diverse backgrounds, perspectives, and experiences.

Join D-ID’s research team to develop the next generation of multimodal video diffusion models and bring cutting-edge research into real-time products used at global scale. About the Team Our research team is small, fast-moving, and highly impactful. We develop multimodal generative models for real-time video creation, turning cutting-edge research into scalable products. We are looking for researchers with deep expertise in generative video to join a team at the core of D-ID’s technology and help shape the future of generative AI. Why Work at D-ID? • Work on cutting-edge video-generation technology at the forefront of AI. • See your research become part of products used at global scale. • Own meaningful research and engineering challenges as part of a small, high-impact team. • Help solve complex problems in real-time video generation. • Build technology that brings the next generation of AI assistants to life. Role & Responsibilities • Research, develop, and evaluate generative AI models for video generation. • Design experiments and evaluation methods covering visual quality, temporal consistency, identity preservation, and performance. • Explore, validate, and implement innovative research ideas. • Own the full lifecycle from research and experimentation to production deployment. • Build models and systems that perform reliably at scale and in real time. • Collaborate closely with research, engineering, and product teams. You are • A curious researcher and dedicated self-learner. • Independent, proactive, and self-motivated. • A hands-on problem solver who is comfortable navigating open-ended research challenges. • A collaborative colleague who enjoys working across disciplines. • Comfortable working in a fast-paced, high-impact environment. Requirements • M.Sc., Ph.D., or equivalent industry experience. • Strong foundation in mathematics. • Expertise in image processing and computer vision. • A strong research track record in generative modeling, computer vision, or a related field. • Strong programming and software design skills. • Hands-on experience training video diffusion models. • Deep understanding of modern generative-model architectures and training methods. How to stand out in the crowd • Experience with multimodal models. • Experience optimizing model inference. • Trained large scale models over cloud infrastructure. About Us D-ID’s generative AI technology transforms customer experience, learning and development, sales, and marketing through video. Our platform enables creators to generate photorealistic digital presenters from text—dramatically reducing the cost and complexity of producing video content at scale and real time. Our customers include most of the Fortune 1000 companies, and organizations across financial services, automotive, technology, retail, entertainment, marketing, production, and social media. Founded in 2017 and backed by leading venture capital firms, D-ID makes its technology available through a self-service studio, API, and plug-ins. Our technology powers lifelike AI assistants and other interactive digital experiences. To date, more than 150 million videos have been created using D-ID’s technology, and over 200,000 developers have used our API. Now it’s your perfect time to join us!

Description About Us: Zenity is the leader in AI Agent Security and the first company to bring an agent-centric security platform to market. As enterprises accelerate AI agent adoption, we are establishing the security framework for how AI agents are secured and governed at enterprise scale. We deliver full-lifecycle visibility, governance, detection, prevention, and response for AI agents from build time to runtime, across SaaS, home-grown platforms, and end-user devices. Backed by $180M+ in total funding, including a $125M Series C led by Norwest, with participation from SoftBank Vision Fund 2 and Microsoft's M12, Zenity is trusted by Fortune 500 and Global 2000 enterprises worldwide. Join us in shaping how AI agents are secured at enterprise scale. About the Role: This is a research‑first role focused on deeply understanding LLM internals to improve the security of AI agents. You’ll design careful experiments on activations and interpretable features- e.g., probing, attribution & ablation/patching, representation‑geometry analyses-to uncover mechanisms behind jailbreak, indirect prompt injection, and other attacks. Then translate those insights into signals that can be used for detection and analysis of a model response. The field of LLM interpretability at scale is exploding, with several major publications in the last months, and major opportunities for innovation. What You’ll Do Responsibilities: • Investigate model internals, including activation/features analysis, unsupervised clustering, discovery of directions in latent space, etc. It may also require training specific model parts to improve interpretability metrics. • Design security‑grounded evaluations: curate datasets for different attack types, evaluate performance of different white box (model internals) methods compared to black box (input/output only) baselines. • Publish and share: produce Zenity Labs posts and open artifacts; when the work is strong, aim for tier‑1 ML venues (NeurIPS, ICML, etc.) and security forums. A publication of code and/or trained models in cases of community relevant novelty. • Build tools: Several open source libraries exist (like Anthropic’s attribution graphs infra), but the research in the field is very dynamic, which will require you to build and adapt tools to your own research directions. This also includes agents to automate research work and distill knowledge from designed experiments. Requirements Requirements: • Deep learning expertise with a track record of non‑trivial research (industry or academia) in LLMs or other domains (e.g., CV, speech). We care that you’ve changed models or methods in meaningful ways (architecture/training/eval), not just used them. • Strong experimental design and scientific writing; comfort pre‑registering hypotheses, testing causal claims, proposing novel directions in a fast-changing field. • PhD or equivalent research experience in the industry (5+ years in a leading research team). Publication record or a portfolio of high‑impact open artifacts will make you stand out from the crowd. • Familiarity with AI frameworks (e.g., HuggingFace Transformers, LangChain, scikit-learn, PyTorch); Experience with a production grade codebase with several contributors is a bonus. • Experience in data analysis: visualization, exploration, cleanup. • Knowledge in GenAI tools such as LLM Orchestrations and integration packages, Agents, RAG systems - a bonus.

Description We are seeking a highly technical, hands-on Principal AI Research Cybersecurity Scientist to drive fast-paced research in frontier AI models, benchmarking, and evaluation. The ideal candidate combines strong research credentials with exceptional engineering capabilities and a proven ability to execute rapid research cycles, moving quickly from identifying research questions to building prototypes, running experiments, and delivering actionable results. The role requires deep expertise in LLMs, foundation models, reasoning, agents, and model evaluation, alongside the ability to translate complex customer challenges into measurable research outcomes. Key Responsibilities • Conduct hands-on research in frontier AI models, reasoning, agents, and multimodal systems. • Design, implement, and iterate on AI benchmarks, evaluation frameworks, and experimental pipelines. • Execute short, high-impact research cycles, rapidly moving from hypotheses to experiments, prototypes, and validated findings. • Identify model limitations, evaluation gaps, and emerging research opportunities. • Work directly with customers and technical stakeholders to translate complex challenges into actionable research. • Collaborate with engineering and product teams to turn research findings into practical solutions. Requirements Qualifications • PhD or MSc in Computer Science, AI, Machine Learning, or a related field, with strong relevant research experience. • Strong publication record at leading AI/ML conferences such as NeurIPS, ICML, ICLR, ACL, or equivalent venues. • Exceptional hands-on technical capabilities, including advanced Python, PyTorch, and experience building and evaluating complex AI systems. • Proven ability to independently design, implement, and execute research experiments within short development cycles. • Deep understanding of LLMs, foundation models, benchmarking, and evaluation methodologies. • Experience with frontier AI labs such as OpenAI, Anthropic, or Google DeepMind is a strong advantage. • Strong analytical and communication skills, with the ability to operate effectively in a fast-paced, customer-driven research environment. Preferred Qualifications • Experience with AI for Cybersecurity, including autonomous security agents, vulnerability research, penetration-testing automation, or security operations. • Experience with Security of AI, including LLM red teaming, adversarial machine learning, prompt injection, and agentic AI security. • Familiarity with cybersecurity tools and environments such as CTFs, sandboxed exploitation environments, static/dynamic code analysis, and security testing frameworks. • Experience developing cybersecurity benchmarks or evaluating frontier models on complex security-related tasks. About Alice Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!

Description We are seeking a Senior AI Researcher to lead post-training evaluation, red-teaming, and reinforcement learning (RL) gym audits on open-weight models. The ideal candidate will establish rigorous benchmarking methodologies, evaluate large language models (LLMs) against complex threats like Indirect Prompt Injections (IPI), and construct post-training evaluation pipelines that accurately measure realistic frontier-level security capabilities. Key Responsibilities RL Post-Training & Benchmarking • Execute post-training runs (e.g. GRPO) using mainstream open-weight generalist models against security-focused RL environments, targeting threat vectors like Indirect Prompt Injection (IPI). • Reward Diagnostics & Trace Analysis - Analyze live loss curves and rollout traces to identify reward hacking, lazy policy convergence, and flawed or over/under-specified verifiers. Task & Environment Auditing • Review tasks and multi-turn environments (including tool use, web navigation, and computer use) for realism, threat model accuracy, data distribution, and dataset balance. Performance Reporting (Gym Cards) • Generate comprehensive evaluation cards detailing hill-climbing performance uplift across checkpoints, failure modes, tokens/turns per rollout, and task-level success rates. Integration & Orchestration • Integrate dockerized environments (e.g., Harbor format) into internal training frameworks, optimizing reset/statefulness semantics, concurrency, and throughput ceilings. Requirements Required Qualifications • Technical Background: M.S. or Ph.D. in Data Science, Machine Learning, Computer Science, or equivalent practical experience in deep learning. • RL & Post-Training Expertise: Strong hands-on experience training large-scale models using RL algorithms (e.g. GRPO, PPO) on open-weight architectures. • AI Security Expertise: Solid understanding of LLM vulnerabilities, red-teaming methodologies, and defensive alignment against IPI attacks. • Infrastructure Skills: Proficiency in PyTorch, Docker containerization, and distributed training architectures. • Diagnostic Skills: Ability to analyze agent rollout traces, craft deterministic rubrics/verifiers, and debug complex reward shaping flaws. Preferred Qualifications • Prior experience working with standard RL gym formats, such as Harbor. • Experience evaluating complex agentic workflows in tool-use or web-browser environments. • Familiarity with evaluating open-weight models similar to Llama or Mistral against adversarial workloads. About Alice Alice is a trust, safety, and security company built for the AI era. We safeguard the communicative technologies people use to create, collaborate, and interact- whether with each other or with machines. In a world where AI has fundamentally changed the nature of risk, Alice provides end-to-end coverage across the entire AI lifecycle. We support frontier model labs, enterprises, and UGC platforms with a comprehensive suite of solutions: from model hardening evaluations and pre-deployment red-teaming to runtime guardrails and ongoing drift detection. Alice is widely considered a global leader in online safety and AI security. We have some of the most forward-thinking and passionate minds in the world working to safeguard over 3 billion users across the largest AI and tech platforms. If you're creative and driven to secure the future of AI, we want to hear from you!

About Spacial: At Spacial, we’re redefining how the built world gets designed, engineered, and approved. With decades of combined experience across architecture, engineering, and construction, we’ve felt the industry’s pain points firsthand — slow approvals, endless redlines, and unclear requirements that derail even the best designs. We built Spacial to fix that. Our AI-powered platform automates structural and MEP engineering, transforming 2D plans into permit-ready, code-compliant drawings in days, not months. This isn’t just optimization. It’s a new standard built to give the AEC industry speed, clarity, and control from day one. By connecting architects, engineers, builders, and homeowners on a single platform, Spacial eliminates friction, streamlines approvals, and accelerates how ideas become reality. About the Role: We are seeking a highly innovative AI Researcher to conduct fundamental and applied research, pioneering the next generation of Generative AI solutions. This role is focused on the theoretical and practical advancement of Large Language Models (LLMs), agent-based architectures, and novel algorithms to create transformative solutions for the construction and design industry. You will be responsible for conducting rigorous experimentation, contributing to the research roadmap, and translating groundbreaking research insights into real-world applications. Responsibilities: • Conduct research, design, and implement novel Generative AI systems using LLMs, vision-language models, and advanced agentic frameworks (e.g., LangChain, LlamaIndex). • Develop and optimize cutting-edge algorithms and methodologies for LLM fine-tuning, retrieval-augmented generation (RAG) optimization, and advanced context engineering. • Perform rigorous experimentation and evaluation of novel GenAI-powered solutions to push the boundaries of model efficiency, performance, and robustness. • Collaborate closely with engineering teams to guide the technical translation of research prototypes into production-grade, high-impact AI products. • Contribute to the long-term AI research direction for the company, staying at the forefront of emerging techniques and academic breakthroughs. • Develop and implement computer vision algorithms that significantly enhance the performance and functionality of our product. Qualifications: • Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a closely related quantitative field (Mathematics, Physics, Electrical Engineering, Computational Biology, etc.). • Minimum of 5+ years of combined experience in AI/ML research and development, with a deep focus on Generative AI, LLMs, and Deep Learning. Required Skills: • A strong, demonstrable track record of research impact, including a history of publications in top-tier conferences (e.g., NeurIPS, ICML, ICLR, AAAI, CVPR, ICCV, ACL) or significant open-source contributions/patents in AI/ML. • Expertise in the theory and practical application of LLM fine-tuning, advanced RAG architectures, and complex agentic systems. • Exceptional proficiency in Python and deep expertise with major ML/Deep Learning frameworks (PyTorch, TensorFlow, Hugging Face Transformers). • Strong foundation in software engineering and algorithm development, with experience working with large datasets. • Exceptional problem-solving, creative thinking, and analytical skills. Preferred Skills: • Experience with multimodal AI (vision-language models, diffusion models). • Familiarity with the challenges and real-time considerations for managing AI workloads in a production environment. • Knowledge of parallel computing and optimization techniques for large-scale model training and inference. Why Join Us? Opportunity to define and shape the future of AI-powered solutions at the critical intersection of fundamental research and real-world product impact. Work directly on cutting-edge GenAI technologies with the potential for a significant global impact in the construction and design industry. A collaborative, innovative startup environment with direct access to experienced founders. Flexible hybrid work arrangement. If you are a pioneering researcher passionate about pushing the theoretical and practical boundaries of Generative AI, we would love to hear from you.

Develop cutting-edge AI methods to design and optimize antibodies, advancing therapeutic programs and Scala's protein design platform. Scala Biodesign is a biotech startup pioneering computational protein design platforms that power the next generation of biologics and industrial enzymes. Built on over a decade of research at the Weizmann Institute of Science, Scala's technology is trusted by ten of the world's top twenty pharmaceutical companies and by global leaders in chemical production. Our platform has been used to design antibodies, complex drug targets, and enzymes, including a malaria vaccine candidate currently in Phase II clinical trials. Our platforms fuse physics-based modeling, AI, and evolutionary data and have been shown in numerous cases to optimize key properties such as potency, manufacturability, and stability under industrially relevant conditions, delivering major performance gains in a single design round and significantly reducing experimental costs. We are looking for an Applied AI Researcher to join our multidisciplinary Antibody team composed of computational biologists, mathematicians and protein designers. In this role, you will drive the development and application of advanced machine learning methods to design and optimize antibodies, contributing directly to cutting-edge therapeutic programs and to the evolution of Scala's computational platform. Responsibilities: - Develop and apply cutting-edge AI/ML methods for antibody design, including generative modeling and protein language models - Design and implement algorithms for multi-objective optimization of antibodies (e.g., affinity, specificity, stability, developability) - Build tools to support iterative design cycles, combining computational predictions with experimental feedback - Collaborate closely with experimental and computational teams to translate models into impactful design outcomes - Stay current with advances in machine learning, structural biology, and AI-driven protein design Requirements: - Ph.D. in Computer science, Physics, Mathematics, computational biology or related field with 2+ years of industry experience, or an M.Sc. with 5+ years of relevant industry experience. - Strong proficiency in Python and PyTorch, with hands-on experience training and fine-tuning deep learning models on GPUs. - Strong algorithmic thinking and problem-solving skills, with the ability to translate theoretical ideas into practical solutions. - Strong communication and collaboration skills. - Fast learner and proven ability to master new domains. - Advantage: Proven experience developing and applying machine learning models to biological or chemical data. Experience with antibody modeling and design (sequence, structure, or interaction prediction). - Advantage: experience profiling and optimizing GPU workloads.

Job Description GM Israel (Herzliya) takes a significant part in introducing sophisticated software features into car in many domains like connected cars, advanced camera technologies and research. We shape the face of the future vehicles in diverse fields by developing cutting edge technologies that define how drivers experience safety, awareness, and confidence on the road. GM is committed to Zero Emission, Zero Crashes and Zero Congestion vision. About the Group At the autonomous vehicles Foundational AI Research team in Israel, which is part of the GM AV AI Research organization, we are shaping next-generation autonomous driving, L3 and beyond. The AI Research organization is dedicated to advancing the state of the art in AI for autonomous vehicles. We are a collaborative, forward-thinking group of researchers and engineers tackling some of the most complex challenges in autonomy and machine learning. About the Role As a Gen AI Staff Researcher, you will contribute deep technical expertise to a collaborative research team developing generative world models, with a focus on the design and large-scale training of diffusion models for autonomous driving. You will research and develop models that learn the dynamics of driving environments and generate realistic, temporally consistent, and controllable future scenarios, conditioned on sensor observations, actions, and scene context. You will contribute hands-on throughout the research lifecycle, from exploring new ideas to large-scale experimentation and implementation, advancing model architectures, training objectives, data strategies, and evaluation methods. As an expert member of the team, you will bring scientific rigor, share technical knowledge, and work closely with fellow researchers and partners in Perception, Behavior/Policy, Data, Simulation, and Validation to translate generative AI advances into measurable improvements in autonomy KPIs. You will also contribute high-quality publications at top-tier conferences and journals and collaborate with leading academic partners. At the GM Foundational AI Research group, your work will influence millions of drivers worldwide and define what’s next in autonomous driving. If you're passionate about solving hard problems and advancing the frontiers of generative AI and autonomous driving, we want you on our team. What will YOU do? • Contribute original research and technical expertise to generative world models, with a focus on diffusion-based modeling of driving environments and their dynamics. • Design, build, train, and evaluate large-scale diffusion models for video and multimodal generation, emphasizing temporal consistency, physical plausibility, and controllability. • Implement and optimize large-scale training on distributed, multi-GPU infrastructure, working with fellow researchers and engineering partners to improve training stability, throughput, memory efficiency, and scalability. • Develop action- and context-conditioned world models that generate diverse future scenarios and support counterfactual exploration, closed-loop simulation, and long-tail scenario coverage. • Develop and evaluate data and training strategies for fleet-scale datasets together with the team, including data curation, pretraining, fine-tuning, and targeted generation of challenging driving scenarios. • Develop and apply rigorous evaluation methods that connect generative quality, consistency, and scenario coverage to downstream KPI improvements for the autonomous driving agent. • Collaborate with engineering teams to translate state-of-the-art research into scalable solutions for simulation, synthetic data generation, and autonomy development. • Publish research at top-tier conferences and journals, track emerging advances in generative AI, and incubate technologies aimed at impacting our L3 autonomous driving technology. Your Skills & Abilities (Required Qualifications) • PhD in Computer Science, Electrical Engineering, Robotics, or a related field. Excellent M.Sc. graduates will be considered. • Over 3 years of research experience in generative AI, computer vision, machine learning, or related areas, with demonstrated depth of expertise and impactful contributions to complex research projects. • Deep expertise in diffusion models and hands-on experience designing, training, and evaluating generative models for images, video, or multimodal data. • Hands-on experience with large-scale distributed training of deep learning models, including training stability, performance optimization, and systematic experimentation. • Strong understanding of world modeling and spatiotemporal learning, including temporal consistency, conditioning mechanisms, and learning environment dynamics. • Strong publication record at top-tier AI/ML conferences and journals. • Excellent coding skills in Python and proficiency with modern AI frameworks such as PyTorch. 



About GM Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all. Why Join Us We believe we all must make a choice every day – individually and collectively – to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team. Non-Discrimination and Equal Employment Opportunities General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers. We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire. Accommodations General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.

Description Join Onyx Security and help build the control plane for autonomous AI in a fast-moving, high-impact environment. Onyx is building the control layer that enables enterprises to safely adopt and scale AI agents across the organization, with the visibility, governance, and operational control needed to understand what agents exist, what they do, how they behave, and what risks they introduce. About the role Onyx is looking for an AI Researcher to help build the intelligence behind our AI security platform. This is a hands-on research role focused on understanding how modern large language models and AI agents behave, identifying new attack vectors and protection techniques, and translating cutting-edge research into production-ready capabilities. The intelligence developed by this team is a core differentiator of our platform and a key driver of the company's success. You will work at the intersection of machine learning, LLMs, and cybersecurity, partnering closely with AI engineers and product teams to develop technologies that directly power our product. We're looking for someone who enjoys understanding how neural networks and foundation models work, pushes the boundaries of AI research, and is excited to see their work deployed into production and used by customers. What you will do • Research the behavior, capabilities, and limitations of modern large language models and AI agents. • Design novel techniques for detecting, evaluating, and proactively protecting against AI threats, prompt injection, model misuse, and emerging attack vectors. • Develop new approaches for securing AI systems and improving the intelligence that powers our platform. • Design and run experiments to evaluate model behavior, validate new ideas, and measure the effectiveness of protection techniques. • Build research prototypes and turn them into production-ready capabilities. • Work closely with Product and Engineering to translate research into scalable product features. • Stay current with advances in LLMs, foundation models, post-training techniques, AI security, and AI safety. • Contribute to the long-term technical direction of Onyx's AI security platform. Requirements What you will bring • 3+ years of experience in AI research, applied machine learning, or a related field. • Strong understanding of deep learning, neural networks, transformer architectures, and large language models. • Hands-on experience training, fine-tuning, evaluating, or post-training modern machine learning models. • Strong Python skills and experience with machine learning frameworks such as PyTorch. • Experience designing rigorous experiments and evaluating model performance. • Ability to translate research into production-ready systems. • Strong analytical thinking and excellent communication skills. Nice to Have • Experience with AI security, AI safety, adversarial machine learning, or robust machine learning. • Experience developing or evaluating autonomous AI agents, reasoning models, or agentic workflows. • Experience with supervised fine-tuning, model optimization, post-training techniques, or reinforcement learning. • Publications in leading AI conferences (NeurIPS, ICML, ICLR, ACL, EMNLP, etc.) or impactful applied research in industry. • Experience deploying machine learning models into production and building scalable AI-powered products.

What We're About Apiiro is the Agentic AppSec Platform built to transform how development teams design, develop, and deliver secure software. Powered by Deep Code Analysis, we give security and engineering teams the risk context they need to ship fast without cutting corners. As pioneers in ASPM, we're not just keeping up with the AI era. We're defining what secure development looks like inside it. About the Team Our Research team operates like a startup inside Apiiro: strategic, high-ownership, and working directly with leadership. We drive the innovation behind Apiiro's AI-native platform, researching and prototyping the next generation of capabilities and guiding both product and go-to-market teams in bringing them to customers. We work at the edge of the security industry, envisioning and building first-of-their-kind, category-defining agentic development security solutions. What You Will Do • Research and prototype novel approaches to application security that go beyond traditional AppSec tooling. • Build proofs-of-concept for advanced prevention, detection, triage, and remediation capabilities. • Design experiments and validate new security features through data-driven testing. • Partner with product and engineering to bring successful POCs into the core platform. • Evaluate and optimize LLM-based agents and model outputs for security use cases. What You're About • 5+ years building security solutions, with deep-level understanding of code security: attack patterns, detection methods, and contextual remediation. • You know how to scientifically tell truth from information: distill signal from noise and extract exceptional results out of AI agents. • Strong research and engineering fundamentals, with hands-on experience building new solutions from scratch. • A problem-solver mindset: you learn fast and approach unfamiliar problems with curiosity. • A proactive team player who takes ownership and helps the team move faster. What We Stand For at Apiiro Customer-First. Our customers are partners, not just clients. We anticipate their needs, go above and beyond to prove business outcomes, and measure our success by theirs. Excellence Mindset. We set the bar high, embrace challenges with curiosity, and never settle. Good enough isn't in our vocabulary. OneTeam. One mission, collective ownership, no silos. Our strength is in how we show up for each other and for our customers. Accountability. We own our actions, our commitments, and our results. Integrity and follow-through are built-in. Most companies react to security. We believe it should be built in from the start. If that mission resonates, let's talk.