AI Researcher jobs in Israel

Simply’s mission is to make the pursuit of creative hobbies simple and fun. Our top-grossing apps Simply Piano, Simply Guitar, Simply Sing, and Simply Draw put us on the fast track to building the world’s largest global consumer subscription service that’s revolutionizing how we spend our time at home. With over a million monthly downloads and hundreds of thousands of daily learners around the world, we’re redefining creative learning at scale. What Senior AI Research Engineers do at Simply Senior AI Research Engineers at Simply develop algorithmic solutions that power new innovative features and continuously improve existing ones, with a strong emphasis on training AI / ML models as a core part of the role. The work spans a wide range of domains - from training generative AI and LLM-based models to create musical content at scale for Simply Piano, through building deep learning computer vision models that enhance user drawings in Simply Draw, to developing real-time audio ML models for music transcription that elevate feedback in Simply Guitar. You will take full end-to-end ownership of cutting-edge algorithms and AI models - leading the process from ideation and research, through development, to production-grade implementation and engineering within Simply’s products. This includes not only designing and building AI models, but also ensuring robust, efficient, and scalable integration into the app - directly shaping the experience of millions of users. Who you are and what you’ve done • 3+ years of experience in designing and implementing AI/ML algorithms, with a strong focus on signal processing • Master's degree in Computer Science, Electrical Engineering, or a related field, or equivalent experience • Proven experience working across the full ML lifecycle - from data acquisition and model training to production implementation and ongoing product iteration • Moves fast, with strong engineering instincts, able to choose the right level of complexity to drive real-world impact • A get things done attitude with a strong sense of ownership • A team player with excellent communication and collaboration skills; able to convey complex ideas clearly to technical and non-technical partners • Exceptional analytical and problem-solving skills • A fast learner, willing to try things out of your comfort zone • Experience in speech, audio, or music-related domains - Advantage

About Fundamental Fundamental is an AI research lab pioneering the future of enterprise decision-making. Our flagship model, NEXUS is the world's most powerful Large Tabular Model (LTM) - purpose-built for the structured records that contain trillions of dollars in business value. With $275m in funding from leading investors and trusted by Fortune 100 companies, Fundamental is giving businesses the Power to Predict. At Fundamental, you'll work on unprecedented technical challenges in foundation model development and build technology that transforms how the world's largest companies make decisions. This is your opportunity to be part of a category-defining company from the ground-up. Join the team defining the future of enterprise AI. Key responsibilities As part of the Research team, you will contribute to ideation, designing, implementing, and evaluating breakthrough Machine Learning models that will be deployed in the real world. Your work will be focused on the entire lifecycle of the models. Alongside the rest of the ML researchers in the team, you will be responsible for our models’ performance in every meaning of this word - whether this means achieving high evaluation scores through novel architectures and training methods, establishing the evaluation protocols themselves, or implementing methods that allow for efficient training and inference. The greatest research is done through solid engineering, so alongside the research you will also take part in ensuring that our research code allows swift, rapid development and testing of new ideas - both your own and the rest of the team’s. Must have • Strong familiarity with the full research cycle in Machine Learning • Strong fundamentals of software engineering • Strong knowledge of Python, and its ML frameworks • Experience with: • Full lifecycle of AI model development • ML infrastructure frameworks and tools • Developing new ML methods, algorithms and models • GPUs (or TPUs) and distributed training • Scaling up models and training regimes • Knowledge of: • Classical ML methods and algorithms • Deep Learning techniques • Expertise in at least one of the following: • Tabular models, time series models, relational foundation models, structured data, large-scale foundation models Nice to have • Published research at AI conferences • Contributions to open source ML projects • Experience working with tabular data / predictive analytics • High Kaggle rank • BSc/MSc/PhD in computer science/machine learning Benefits • Competitive compensation with salary and equity • Comprehensive health coverage for you and your dependents • Paid parental leave for all new parents, inclusive of adoptive and surrogate journeys • Relocation support for employees moving to join the team in one of our office locations • A mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action

Applied AI Scientist We're hiring an exceptional Applied AI Scientist to join our team! In this role, you'll design and deploy enterprise-grade AI agents that drive real business impact across Tipalti's core functions - Sales, Marketing, Customer Success, Customer Support, Risk, and Finance. You'll be building agentic systems that execute complex, multi-step business workflows end-to-end. The ideal candidate is a hands-on builder with deep AI expertise who thrives on turning complex business problems into reliable, production-grade AI systems. Why join Tipalti? Tipalti is the AI-powered platform for finance automation, elevating how finance teams operate in the global economy. We empower our customers to scale faster and smarter by removing the complexities of doing global business and accelerating their finance operations efficiency. Our platform provides a comprehensive suite of finance automation solutions designed for mid-market businesses across accounts payable, global payouts, procurement, employee expenses, corporate cards, supplier management, tax compliance, and treasury. Tipalti partners with leading financial institutions such as Citi, Wells Fargo, J.P. Morgan, and Visa, enabling over 5,000 global companies to efficiently and securely pay millions of suppliers and payees across 200+ countries and territories, in 120 currencies. At Tipalti, we pride ourselves on our collaborative culture, the quality of our product and the capabilities of our people. Tipaltians are passionate about the work they do, and keen to get the job done. Tipalti offers competitive benefits, a flexible workplace, and an environment where diverse individuals can thrive and make an impact. Our culture ensures everyone checks their egos at the door and stands ready to reach for success together. Founded in Israel in 2010, Tipalti is a global business headquartered in the San Francisco Bay Area (Foster City) with offices in Tel Aviv, Plano, Toronto, Vancouver, London, Amsterdam, Tbilisi and Medellin. In This Role, You Will Be Responsible For • Enterprise AI Agent Development: Designing, building, and deploying AI agents that automate and augment high-value workflows across business functions - including lead qualification and outreach (Sales & Marketing), churn reduction(Customer Success), and Ticket deflection (Support). • 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 suited for an enterprise fintech environment. • Knowledge Systems: Building and maintaining RAG pipelines that ground agents in Tipalti's proprietary knowledge - product documentation, customer data, financial records, and internal playbooks - using vector databases, hybrid search, and re-ranking. • 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. • Cross-Functional Collaboration: Partnering with stakeholders across the company to define agentic use cases, translate business requirements into technical features, and deliver products that create measurable ROI - from data preprocessing through product deployment. About You • Bachelor’s degree in Computer Science, Engineering or a related field, with focus on AI. • 2.5-5 years of hands-on experience in AI/ML engineering, ideally within the fintech industry or a related sector, with a track record of deploying AI agents or agentic workflows in production • Proficiency in Python and SQL for data manipulation, analysis, and AI system building. • Deep experience with LLMs and prompt engineering, including systematic evaluation of enterprise AI solutions • Experience with building RAG systems and Conversational chatbots - Advantage • Experience with cloud platforms (AWS preferred) for deployment and AI-Ops practices. • Analytical Mindset: You bring strong statistical reasoning and business acumen, with the ability to critically assess AI solutions and their real-world impact. • Project Management: You can manage and prioritize multiple tasks, balancing short-term and long-term goals to deliver timely, high-impact results. Why join Tipalti? Tipalti is the AI-powered platform for finance automation, elevating how finance teams operate in the global economy. We empower our customers to scale faster and smarter by removing the complexities of doing global business and accelerating their finance operations efficiency. Our platform provides a comprehensive suite of finance automation solutions designed for mid-market businesses across accounts payable, global payouts, procurement, employee expenses, corporate cards, supplier management, tax compliance, and treasury. Tipalti partners with leading financial institutions such as Citi, Wells Fargo, J.P. Morgan, and Visa, enabling over 5,000 global companies to efficiently and securely pay millions of suppliers and payees across 200+ countries and territories, in 120 currencies. At Tipalti, we pride ourselves on our collaborative culture, the quality of our product and the capabilities of our people. Tipaltians are passionate about the work they do, and keen to get the job done. Tipalti offers competitive benefits, a flexible workplace, career coaching, and an environment where diverse individuals can thrive and make an impact. Our culture ensures everyone checks their egos at the door and stands ready to reach for success together. Founded in Israel in 2010, Tipalti is a global business headquartered in the San Francisco Bay Area (Foster City) with offices in Tel Aviv, Plano, Toronto, Vancouver, London, Amsterdam, Tbilisi and Medellin. Our tech teams are the engine behind our business. Tipalti’s tech ecosystem is extremely rich and we continually add new features to our products, ensuring that we respond to our clients’ needs at scale. Our tech teams retain a fast-paced, start-up vibe that encourages innovation and critical thinking. At Tipalti, you’ll have the opportunity to work with a diverse, global team of engineers, developers and product leaders who are collectively building the future of our best-in-class product suite as we transform financial operations for the future. About Our Tel Aviv Offices: Hybrid Work Model - Tipalti offers a hybrid work model, with two days per week working from home and three days per week from our beautiful offices in North Tel Aviv. Shuttle Services - Shuttle services are available from the nearest train station and across Tel Aviv to the office. Parking - Parking is available for all employees. Snacks & Treats - Enjoy a selection of snacks and treats available on every floor. #LI-hybrid Our Mission Our mission is to elevate how finance teams operate in the global economy. We empower our customers to scale faster and smarter by removing the complexities of doing global business and accelerating their finance operations efficiency. We are the AI-powered platform that automates finance. Tipalti is fueled by a commitment to our customers and a desire to build lasting connections. Our client portfolio includes high-velocity businesses such as Amazon Twitch, GoDaddy, Roku, WordPress.com, and ZipRecruiter. We work hard for our 99% customer retention rate which is built on trust, reliability and innovation. Tipalti means we handled it" - a mission to which we are constantly committed. Accommodations Tipalti champions inclusive teams, in which every voice counts. We are committed to recruiting diverse candidates with varied personal experiences and abilities. We welcome applications from candidates belonging to historically underrepresented or disadvantaged groups, and maintain an equitable Talent Acquisition process that is free from discrimination. As an equal opportunities employer, Tipalti complies with employment and human rights laws across the various jurisdictions in which we operate. Should you require reasonable adjustments or accommodations during the recruitment process, including access to alternate formats of materials, meeting spaces, or other accommodations that could better enable your full participation, please reach out to [email protected] for assistance. AI Use We may use artificial intelligence and automated systems (collectively "AI") to screen, assess, and select candidates during our recruitment process. This includes resume screening, skills assessment, and candidate matching. You have the right to request human review of any automated decision. For more information about how we collect and use personal data and information during recruitment, please refer to our Job Candidate Privacy Notice. For additional questions about our use of AI during our recruitment process, you can contact [email protected]. Privacy We are committed to protecting the privacy interests of job applicants and candidates. For more information about our privacy practices during our Talent Acquisition process, please refer to our Job Candidate Privacy Notice below: Job Candidate Privacy Notice | Tipalti www.tipalti.com/privacy/job-candidate-privacy-notice/

Description Vega is one of the fastest-growing startups in cybersecurity, redefining security analytics and operations with an AI-native platform for the SOC. We are building the next-generation operating system for security teams. Vega is already delivering real impact at some of the world’s largest organizations - improving detection, unlocking the value of their security data, and reducing cost and complexity. With HQs in New York and TLV, we're looking for people who want to be a part of the next rocket-ship in cyber. As an AI Researcher, you’ll be part of the team building the AI systems that power our products. You’ll work across research and engineering - from training and post-training state-of-the-art LLMs to applying them to challenging real-world problems such as agentic behavior, coding, and security-related decision-making. This is a hands-on research role with a strong focus on taking ideas from experimentation to production. You’ll have significant ownership and the opportunity to shape both the direction of our AI research and the systems we build around it. WHAT YOU WILL DO • Train, adapt, and scale state-of-the-art LLMs using techniques such as post-training SFT, knowledge distillation, LoRA, and reinforcement learning. • Develop and evaluate new algorithms and approaches, bridging cutting-edge academic research with production-grade AI systems. • Optimize models for production, balancing quality, latency, throughput, and cost at scale. • Own the AI lifecycle—from algorithmic prototyping and synthetic data generation to evaluation, deployment, and iteration of production AI features. • Work closely with engineering and product teams to translate research advances into impactful AI capabilities. • Lead research initiatives that advance the capabilities of Vega’s AI systems. Requirements WHAT YOU WILL BRING • 5+ years of professional experience as a research scientist, applied scientist, or algorithms/ML engineer. • Ph.D. or Master’s degree in computer science, machine learning, data science, statistics, or a related field. • Expert-level proficiency in PyTorch and deep learning training and inference optimization. • Hands-on experience training, fine-tuning, evaluating, or optimizing large-scale LLMs in research or production environments. • Strong Python programming skills and experience writing production-grade ML code. • Experience working with large-scale data and ML infrastructure. NICE TO HAVE • Experience applying AI/ML to cybersecurity, including threat detection, incident response, log analysis, or related problems. • Experience with reinforcement learning or preference optimization for LLMs. • A track record of research publications, open-source contributions, or other technical work demonstrating research depth.

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.

Mobileye is a pioneering force in the autonomous vehicles (AV) industry. Join us to build the brain behind the car — a large-scale, multi-task neural network that powers the core of Mobileye’s autonomous stack. You’ll design and train cutting-edge deep learning models tailored for our custom EyeQ chip, tackling end-to-end challenges and deploying real-world solutions. From novel architectures and advanced training techniques to performance tuning under tight constraints, you’ll work closely with software and hardware teams to turn research into high-impact, production-ready systems. If you’re a brilliant, hands-on researcher with a passion for shaping the future — this is your launchpad. Our team is at the forefront of Mobileye’s most advanced AI efforts. As a central hub for deep learning innovation, we’re trusted with designing the core neural network architecture that powers the company’s flagship products. If you’re seeking a high-impact role among top-tier researchers and developers — this is the place to be. All you need is: • PhD in Computer Science or a related discipline (exceptional MSc candidates will be considered). • 4+ years of hands-on experience developing deep learning algorithms in Python. • Experience building end-to-end DL pipelines: data preparation, training, evaluation, and deployment. • Proficiency in at least one deep learning framework (e.g., TensorFlow, PyTorch). • Excellent problem-solving skills and a research-oriented mindset. Advantages: • Industry experience in DL or software development. • Familiarity with hardware-aware model optimization. • Experience with cloud platforms (e.g., AWS), Docker, and Linux environments. • Publications or contributions in the fields of deep learning, neural architecture search, knowledge distillation or multi-task learning. Mobileye changes the way we drive, from preventing accidents to semi and fully autonomous vehicles. If you are an excellent, bright, hands-on person with a passion to make a difference come to lead the revolution!

The CTO Group is a small, elite team focused on the decision-making module of Mobileye's autonomous driving system. Our mission is to solve some of the hardest problems in autonomous driving by combining the full spectrum of modern computer science - from rigorous mathematical modeling, optimization, and algorithm design to deep learning. The team develops the driving policies that translate system-wide inputs into safe, efficient, and human-like driving behavior. Our work spans classical algorithms, optimization under constraints, probabilistic reasoning, reinforcement & supervised learning, all grounded in real-world driving data. The group is comprised of top researchers and developers and is led by world-class scientists, offering a unique opportunity to work closely with the CTO, shape the future of autonomous driving, and influence the company's technical direction. What will your job look like: • Research and develop innovative algorithms for autonomous driving planning and decision-making. • Model complex real-world driving scenarios and formulate them as optimization, learning, or algorithmic problems. • Apply a broad range of techniques - from mathematical modeling and classical algorithms to machine learning and deep learning - to improve driving policies. • Analyze large-scale driving data to gain insights, validate hypotheses, and improve system robustness and performance. • Design and implement high-quality production-ready code in a research-driven environment. • Read, evaluate, and build upon state-of-the-art scientific literature in algorithms, AI, and machine learning. All you need is: • 5+ years of experience in algorithm development, machine learning, or AI research. • Outstanding MSc in Computer Science, Computer Engineering, Mathematics, Physics, or a related quantitative field. • PhD - an advantage. • Strong programming skills in C++ and Python. • Outstanding mathematical and analytical abilities. • Passion for solving challenging research problems and the ability to quickly learn from scientific literature. Mobileye changes the way we drive, from preventing accidents to semi and fully autonomous vehicles. If you are an excellent, bright, hands-on person with a passion to make a difference come to lead the revolution!

Build the intelligence behind the next driving decision. We’re building a reinforcement-learning driving planner for complex, interactive road scenarios. We’re looking for a researcher to help take it from simulation to real vehicles. You’ll develop policy models, rewards, and training methods. You’ll define how driving behavior is evaluated, analyze failures in closed loop, and validate improvements on the road. You’ll work in a small team at Mobileye and collaborate with control and other algorithm teams. This is a high-impact role with direct influence on a core part of Mobileye’s driving technology and its future products. What will your job look like? • Research and develop reinforcement-learning planning algorithms, including policy architectures, reward design, training objectives, and optimization methods. • Train and evaluate RL policies for difficult, interactive driving scenarios, building on the existing learning-based planner and complementary classical components. • Develop evaluation methods and relevant metrics for safety, progress, comfort, and interaction quality, and use them to guide experiments and analyze failures. • Build simulation-based training and closed-loop evaluation workflows. • Turn research ideas into reliable components of the driving stack. All you need is: • M.Sc. or Ph.D. in Computer Science, Electrical Engineering, or a related field. • 3+ years of hands-on industry experience in deep learning, including designing and training neural networks. • Hands-on reinforcement-learning experience through research or practical application. • Experience in autonomous driving, robotics, motion planning, simulation, or closed-loop evaluation- an advantage Mobileye changes the way we drive, from preventing accidents to semi and fully autonomous vehicles. If you are an excellent, bright, hands-on person with a passion to make a difference come to lead the revolution!

The CTO Group is a small, elite team focused on the decision-making module of Mobileye's autonomous driving system. Our mission is to solve some of the hardest problems in autonomous driving by combining the full spectrum of modern computer science - from rigorous mathematical modeling, optimization, and algorithm design to deep learning. The team develops the driving policies that translate system-wide inputs into safe, efficient, and human-like driving behavior. Our work spans classical algorithms, optimization under constraints, probabilistic reasoning, reinforcement & supervised learning, all grounded in real-world driving data. The group is comprised of top researchers and developers and is led by world-class scientists, offering a unique opportunity to work closely with the CTO, shape the future of autonomous driving, and influence the company's technical direction. What will your job look like: • Research and develop innovative algorithms for autonomous driving planning and decision-making. • Model complex real-world driving scenarios and formulate them as optimization, learning, or algorithmic problems. • Apply a broad range of techniques - from mathematical modeling and classical algorithms to machine learning and deep learning - to improve driving policies. • Analyze large-scale driving data to gain insights, validate hypotheses, and improve system robustness and performance. • Design and implement high-quality production-ready code in a research-driven environment. • Read, evaluate, and build upon state-of-the-art scientific literature in algorithms, AI, and machine learning. All you need is: • 5+ years of experience in algorithm development, machine learning, or AI research. • Outstanding MSc in Computer Science, Computer Engineering, Mathematics, Physics, or a related quantitative field. • PhD - an advantage. • Strong programming skills in C++ and Python. • Outstanding mathematical and analytical abilities. • Passion for solving challenging research problems and the ability to quickly learn from scientific literature. Mobileye changes the way we drive, from preventing accidents to semi and fully autonomous vehicles. If you are an excellent, bright, hands-on person with a passion to make a difference come to lead the revolution!

Build the intelligence behind the next driving decision. We’re building a reinforcement-learning driving planner for complex, interactive road scenarios. We’re looking for a researcher to help take it from simulation to real vehicles. You’ll develop policy models, rewards, and training methods. You’ll define how driving behavior is evaluated, analyze failures in closed loop, and validate improvements on the road. You’ll work in a small team at Mobileye and collaborate with control and other algorithm teams. This is a high-impact role with direct influence on a core part of Mobileye’s driving technology and its future products. What will your job look like? • Research and develop reinforcement-learning planning algorithms, including policy architectures, reward design, training objectives, and optimization methods. • Train and evaluate RL policies for difficult, interactive driving scenarios, building on the existing learning-based planner and complementary classical components. • Develop evaluation methods and relevant metrics for safety, progress, comfort, and interaction quality, and use them to guide experiments and analyze failures. • Build simulation-based training and closed-loop evaluation workflows. • Turn research ideas into reliable components of the driving stack. All you need is: • M.Sc. or Ph.D. in Computer Science, Electrical Engineering, or a related field. • 3+ years of hands-on industry experience in deep learning, including designing and training neural networks. • Hands-on reinforcement-learning experience through research or practical application. • Experience in autonomous driving, robotics, motion planning, simulation, or closed-loop evaluation- an advantage Mobileye changes the way we drive, from preventing accidents to semi and fully autonomous vehicles. If you are an excellent, bright, hands-on person with a passion to make a difference come to lead the revolution!

Mobileye is a pioneering force in the autonomous vehicles (AV) industry. Join us to build the brain behind the car — a large-scale, multi-task neural network that powers the core of Mobileye’s autonomous stack. You’ll design and train cutting-edge deep learning models tailored for our custom EyeQ chip, tackling end-to-end challenges and deploying real-world solutions. From novel architectures and advanced training techniques to performance tuning under tight constraints, you’ll work closely with software and hardware teams to turn research into high-impact, production-ready systems. If you’re a brilliant, hands-on researcher with a passion for shaping the future — this is your launchpad. Our team is at the forefront of Mobileye’s most advanced AI efforts. As a central hub for deep learning innovation, we’re trusted with designing the core neural network architecture that powers the company’s flagship products. If you’re seeking a high-impact role among top-tier researchers and developers — this is the place to be. All you need is: • PhD in Computer Science or a related discipline (exceptional MSc candidates will be considered). • 4+ years of hands-on experience developing deep learning algorithms in Python. • Experience building end-to-end DL pipelines: data preparation, training, evaluation, and deployment. • Proficiency in at least one deep learning framework (e.g., TensorFlow, PyTorch). • Excellent problem-solving skills and a research-oriented mindset. Advantages: • Industry experience in DL or software development. • Familiarity with hardware-aware model optimization. • Experience with cloud platforms (e.g., AWS), Docker, and Linux environments. • Publications or contributions in the fields of deep learning, neural architecture search, knowledge distillation or multi-task learning. Mobileye changes the way we drive, from preventing accidents to semi and fully autonomous vehicles. If you are an excellent, bright, hands-on person with a passion to make a difference come to lead the revolution!

How do you generate a driving scene that stays consistent over time, across cameras, and under controlled changes? These are exactly the types of problems we solve. Mobileye’s Visual GenAI team develops image and video generation capabilities for autonomous driving, with a growing focus on video and world models. We’re looking for a hands-on researcher to help shape our research direction and turn ideas into working capabilities, with access to large proprietary driving datasets and close collaboration with the teams developing Mobileye’s next generation of autonomous driving technology. What will your job look like: • Research and develop image and video generation models, with a focus on temporal consistency, multiview coherence, and controllable driving-scene generation. • Explore and adapt state-of-the-art world models for autonomous driving, helping shape the team’s research and technical direction. • Own the full development lifecycle, from research and experimentation to model training, evaluation, and integration into real-world workflows. • Build scalable, clean Python and PyTorch implementations for training and evaluating generative models. • Collaborate with AI researchers and perception teams to develop generative capabilities for training and evaluating autonomous driving systems. All you need is: • M.Sc. or Ph.D. in Computer Science, Electrical Engineering, or a related field. • 3+ years of industry experience in Deep Learning and Computer Vision, preferably working on generative AI or foundation models. • A hands-on approach and the ability to turn research ideas into working solutions. Nice to have: • Hands-on experience training image or video generation models, including diffusion and flow-based models. • Experience with world models, multiview generation, 3D scene representations, or temporal modeling. • Experience training or adapting foundation models, including Vision-Language Models (VLMs) and other multimodal models. • Experience with distributed training and large-scale datasets. • Publications in top-tier conferences such as CVPR, NeurIPS, ICCV, or ECCV. Mobileye changes the way we drive, from preventing accidents to semi and fully autonomous vehicles. If you are an excellent, bright, hands-on person with a passion to make a difference come to lead the revolution!

How do you generate a driving scene that stays consistent over time, across cameras, and under controlled changes? These are exactly the types of problems we solve. Mobileye’s Visual GenAI team develops image and video generation capabilities for autonomous driving, with a growing focus on video and world models. We’re looking for a hands-on researcher to help shape our research direction and turn ideas into working capabilities, with access to large proprietary driving datasets and close collaboration with the teams developing Mobileye’s next generation of autonomous driving technology. What will your job look like: • Research and develop image and video generation models, with a focus on temporal consistency, multiview coherence, and controllable driving-scene generation. • Explore and adapt state-of-the-art world models for autonomous driving, helping shape the team’s research and technical direction. • Own the full development lifecycle, from research and experimentation to model training, evaluation, and integration into real-world workflows. • Build scalable, clean Python and PyTorch implementations for training and evaluating generative models. • Collaborate with AI researchers and perception teams to develop generative capabilities for training and evaluating autonomous driving systems. All you need is: • Ph.D. in Computer Science, Electrical Engineering, or a related field. Exceptional M.Sc. candidates with a specialization in Gen AI will also be considered. • 5+ years of industry experience in Deep Learning and Computer Vision, preferably working on generative AI or foundation models. • A hands-on approach and the ability to turn research ideas into working solutions. Nice to have: • Hands-on experience training image or video generation models, including diffusion and flow-based models. • Experience with world models, multiview generation, 3D scene representations, or temporal modeling. • Experience training or adapting foundation models, including Vision-Language Models (VLMs) and other multimodal models. • Experience with distributed training and large-scale datasets. • Publications in top-tier conferences such as CVPR, NeurIPS, ICCV, or ECCV. Mobileye changes the way we drive, from preventing accidents to semi and fully autonomous vehicles. If you are an excellent, bright, hands-on person with a passion to make a difference come to lead the revolution!

Build the intelligence behind the next driving decision. We’re building a reinforcement-learning driving planner for complex, interactive road scenarios. We’re looking for a researcher to help take it from simulation to real vehicles. You’ll develop policy models, rewards, and training methods. You’ll define how driving behavior is evaluated, analyze failures in closed loop, and validate improvements on the road. You’ll work in a small team at Mobileye and collaborate with control and other algorithm teams. This is a high-impact role with direct influence on a core part of Mobileye’s driving technology and its future products. What will your job look like? • Research and develop reinforcement-learning planning algorithms, including policy architectures, reward design, training objectives, and optimization methods. • Train and evaluate RL policies for difficult, interactive driving scenarios, building on the existing learning-based planner and complementary classical components. • Develop evaluation methods and relevant metrics for safety, progress, comfort, and interaction quality, and use them to guide experiments and analyze failures. • Build simulation-based training and closed-loop evaluation workflows. • Turn research ideas into reliable components of the driving stack. All you need is: • M.Sc. or Ph.D. in Computer Science, Electrical Engineering, or a related field. • 3+ years of hands-on industry experience in deep learning, including designing and training neural networks. • Hands-on reinforcement-learning experience through research or practical application. • Experience in autonomous driving, robotics, motion planning, simulation, or closed-loop evaluation- an advantage Mobileye changes the way we drive, from preventing accidents to semi and fully autonomous vehicles. If you are an excellent, bright, hands-on person with a passion to make a difference come to lead the revolution!

NVIDIA Israel is seeking innovative and driven Applied Researchers in the field of deep learning. We are looking for candidates with a consistent track record of research excellence; a broad perspective across the fields of artificial intelligence; and deep experience in machine learning, applied science, and computational medicine. NVIDIA is a world leader in high-performance and mobile computing technology for AI, with ambitious plans for future systems. This position offers the opportunity to have a real impact in an applied research-focused team in a dynamic company. The Applied AI Architecture group focuses on applied research. As a member of the team, you will publish your work and share code as an open source. In addition, you will join a groundbreaking initiative at the intersection of AI and biology. This collaborative project aims to develop both foundational and generative AI models, as well as agentic AI systems, redefining our understanding of complex biological systems and enabling advanced diagnostics and novel scientific insights, while strengthening NVIDIA’s Health Platform ecosystem. What You'll Be Doing: • Conceptualize, design, and implement novel deep learning architectures for biological data, with a strong focus on large-scale models such as Large Language Models (LLMs), Transformers, and State Space Models (SSMs). • Develop multimodal learning systems that integrate heterogeneous data types (e.g., clinical time-series, imaging, genomics, and text) for improved representation and prediction. • Develop both foundational and generative models and agentic AI systems, including multi-step reasoning, tool use, and autonomous decision-making capabilities. • Develop digital twin systems for healthcare, combining mechanistic models, physiological data, and AI to simulate disease progression, treatment response, and patient-specific trajectories. • Implement deep learning systems integrated with agents, enabling end-to-end workflows that combine learning, planning, and execution. • Evaluate model performance, analyze results, and iterate on designs to achieve optimal outcomes. • Apply your knowledge of distributed training to build high-quality code for training, optimizing, and deploying large-scale models, while managing complex datasets. • Collaborate closely with a diverse team of researchers, bioinformaticians, and domain experts in a highly interdisciplinary environment. What We Need to See: We are looking for individuals who demonstrate a strong foundation in deep learning and a proven ability to translate innovative ideas into practical, scalable systems. • PhD in Machine Learning, Computer Science, Engineering, or a related discipline. • 8+ years of hands-on experience in developing, training, and deploying deep learning models at scale, including LLMs, Transformers, SSMs, and/or generative models. • Experience with multimodal learning and integrating diverse data modalities is highly valued. • Experience with agentic AI frameworks or systems (e.g., tool-augmented models, planning-based agents, or multi-agent systems) is a strong advantage. • Strong expertise in distributed training, optimization, and inference. • Proven ability to lead independent research, implement robust solutions, and rigorously evaluate performance. • Track record of publications and presentations at top conferences. • Strong programming skills in Python and C++, with experience in PyTorch and/or CUDA. • Excellent communication skills and ability to thrive in a dynamic, research-driven team. Mentoring experience is a plus. Ways To Stand Out From The Crowd: • Hands-on experience building advanced AI systems, including agentic AI (RAG, tools, planning, multi-agent) and multimodal models combining vision, language, and structured/time-series data. • Proven track record optimizing large-scale ML systems, with experience in data pipelines and distributed frameworks for LLM-scale data. • Background in bioinformatics or digital biology, with experience working across interdisciplinary teams spanning research, engineering, and clinical domains. • Experience in building or implementing digital twin systems, simulation frameworks, or data-driven modeling in healthcare or related domains is a strong plus. We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided a reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.

We are in search of a top-tier AI Agents applied researcher to work closely with hardware architects and software developers to develop end-to-end agentic systems that drive significant enhancements in NVIDIA's products. Our team propels generative AI forward by building and deploying agentic systems that integrate innovative LLMs with domain tools to expedite HW and SW engineering workflows at scale. What You'll Be Doing: • Build complex agentic systems featuring multi-agent coordination, long-horizon reasoning, and advanced planning frameworks. • Develop full-scale solutions, including domain-specific enterprise agents and high-performance retrieval pipelines (RAG) spanning various data sources. • Develop innovative AI flows to improve hardware and software through collaboration with various engineering roles. • Collaborate with SME's to transform rules of thumb into specific assignments, resources, cues, and guidelines. Define success measures, evaluation data, and feedback loops for agents to make a measurable difference in NVIDIA's HW and SW products. • Set up evaluation backbone using offline golden sets and online telemetry for confident iterations, cost control, and safe improvements. What We Need To See: • BSc/MSc in CS/CE or related field (or equivalent experience) • 10+ years in applied ML/AI or large-scale systems, with 3+ years crafting agentic or LLM-powered applications in production environments. • Proficient in Python; skilled in agentic frameworks, tool use, RAG pipelines, and model adaptation. • Excellence in communication and facilitation: aligning diverse collaborators, documenting decisions/assumptions, and influencing without authority. • Proactive, independent, possessing strong analytical and problem-solving abilities; adept at handling uncertainty to provide practical, gradual benefits. Ways To Stand Out From The Crowd: • Strong software development experience • Experience with data processing and storage (e.g. SQL databases, NoSQL databases). • Networking background, with knowledge of network architectures and networking concepts At the intersection of cutting-edge innovation and global impact, we have cultivated an environment where the world's most brilliant minds thrive. We offer industry-leading compensation and a culture built on excellence. If you are a high-impact applied researcher who lives for complex problem-solving and technical mastery, you belong here. We are an equal-opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request accommodation

We are seeking a Senior Deep Learning Researcher for an excellent opportunity! This role provides an outstanding opportunity to engage in groundbreaking innovation and contribute to advancing diffusion-based technologies. You will work with pioneering methodologies and tools, crafting solutions that push the boundaries of AI capabilities. Joining NVIDIA means being part of a phenomenal team renowned for its inventions, such as NVIDIA Cosmos, Llama-Nemotron, Sana, and contributing to impactful work that influences various applications. We offer a collaborative environment that fosters professional growth. You will have the opportunity to collaborate with some of the brightest minds in the field, both within NVIDIA's global network and with leading companies worldwide, making this role perfect for those passionate about advancing AI technology and eager to make a significant impact on the future of the field. What you'll be doing: • Invent and build ground-breaking techniques for efficient multi-modality model creation and publish the findings in leading journals and conferences. • Combine traditional diffusion technologies with the latest and greatest LLMs. • Contribute to NVIDIA's AI enterprise software to ensure robust and scalable solutions. • Collaborate with internal and external teams worldwide to drive research and development in multi-modal learning, using different professions and resources across the company. • Partner with leading scientific organizations and industry pioneers to remain at the forefront of technological advancements and integrate the latest innovations into practical applications. What we need to see: • PhD. in Computer Science, Electrical Engineering, or a closely related field, or equivalent experience. • At least 3 years of relevant research experience • Publications in prestigious conferences and journals like NeurIPS, ICLR, and CVPR • In-depth understanding and active research experience in leading generative AI techniques, with a track record of contributing to advancements in this area • Extensive experience in image and video understanding, generation, and reasoning. Ways to stand out from the crowd: • High proficiency in programming and coding • Degree from a top-tier institution or equivalent experience in a world-class industrial research group • Substantial contributions to the multi-modality or diffusion forefront of research. • Experience in research fields of LLMs. Candidates should apply with a detailed CV, publication list, and brief research statement.

Cato Networks is the converged network and security cloud for the AI era. As AI reshapes cybersecurity, enterprises face a dual challenge: unlocking AI’s potential while defending against AI-driven attacks. Cato addresses both through a unified, cloud-native platform, providing the visibility and context to prioritize risks and stop threats in real time across users, applications, data, and AI agents. Join us as we scale: take on ambitious technological challenges and shape the next generation of enterprise security at a company trusted by thousands of organizations worldwide. As part of this exciting journey, Cato recently joined forces with Aim Security — a fast-growing innovator redefining how organizations secure and build with AI. Backed by Cato’s global reach and powered by Aim’s startup energy, we’re building the future of AI Security together. We are on a mission to enable enterprises to adopt AI safely and securely. Our approach combines advanced AI research with practical implementation to offer seamless integration and protection for our clients' AI based tools and infrastructure. We are looking for a Senior Data Scientist / Applied AI Researcher with deep expertise in NLP and LLM-based systems, and the ability to operate across the full lifecycle, from problem formulation and research design to production deployment and real-world iteration. You won’t be working on isolated experiments. You’ll be part of a multidisciplinary team that owns the system end-to-end and is responsible for how it behaves under real production traffic. This role requires strong scientific discipline and the maturity to balance innovation with practical constraints. What you’ll do • End-to-End Ownership: Lead AI security solutions from problem formulation and research design through model development, evaluation, and production deployment. Ensure solutions are measurable, reliable, and effective under real-world traffic. • Drive Technical Direction: Take responsibility for ambiguous AI security problems, propose thoughtful approaches, and drive structured experimentation and deep model analysis. • Build for Scale: Design systems that are not only accurate, but scalable, efficient, and robust. • Staying Updated: Continuously explore advances in NLP and LLM-based systems, and critically assess what is worth integrating into a production environment. What you bring • 5+ years of hands-on experience applying NLP/DL algorithms, techniques to real-world problems, with strong intuition for textual data and model behavior. • Experience working with LLMs, with a strong grasp of practical best practices and the judgment to apply them throughout the R&D lifecycle when building task-specific models. • Strong proficiency in Python and modern DL frameworks (PyTorch, HuggingFace, etc.). • Experience designing experiments, defining metrics, and analyzing model failures. • A strong drive to solve complex AI security challenges, with both curiosity and pragmatism. Why join us • Be part of a lean, elite team where your work doesn’t just sit in a backlog — you’ll ship real value, frequently, and see the impact. • Bridge the best of startup energy with the scale and reach of Cato Networks: you’ll build for enterprise-grade reliability and commercial scale, and also retain the innovation spirit of a startup.

Description About us We build the context layer for engineering organizations. We connect code, runtime telemetry, data lineage, and operational systems into one live model of how software runs, then give AI agents that model through chat and MCP. What you'll do • Own the evaluation function for all Cobalt agents: code Q&A, change-impact analysis, incident response, and MCP tool use by coding agents. • Design and build eval harnesses and benchmarks, with ground truth taken from merged PRs, production traces, and code. • Define and track agent performance metrics: recall and precision, cost per correct answer, tool-call efficiency, latency, and failure modes. • Run controlled comparisons across models, prompts, retrieval strategies, and baselines, with statistical rigor. • Diagnose agent failures in retrieval, reasoning, and tool design, and drive the fixes with engineering. • Build regression suites in CI that score every model, prompt, and connector change before release. • Lead external research, including ownership of research papers. • Set the research agenda and mentor future hires. Requirements Requirements • 7+ years in ML/NLP research or applied AI, including evaluating LLMs or agents. • A track record of designing benchmarks: task sampling, contamination control, scoring methods, and power analysis. • Deep knowledge of agent architectures: tool use, retrieval, multi-step planning, MCP or similar protocols. • Expert Python, and production-quality eval infrastructure you have shipped. • Experience leading research projects end to end, from design to publication or product. Nice to have • Publications at NeurIPS, ICLR, ACL, ICSE or FSE on LLM evaluation, code intelligence or agents. • Experience with repo-level code benchmarks (SWE-bench-style). • Experience with LLM-as-judge methods and their known failure modes. • A background in distributed systems, observability data, or large codebases. Why join • Enterprise ground truth: thousands of repos, live traces and production incidents. • Your evals decide what ships. • A founding role in the research function.

Our Mission At Palo Alto Networks®, we’re united by a shared mission—to protect our digital way of life. We thrive at the intersection of innovation and impact, solving real-world problems with cutting-edge technology and bold thinking. Here, everyone has a voice, and every idea counts. If you’re ready to do the most meaningful work of your career alongside people who are just as passionate as you are, you’re in the right place. Who We Are In order to be the cybersecurity partner of choice, we must trailblaze the path and shape the future of our industry. This is something our employees work at each day and is defined by our values: Disruption, Collaboration, Execution, Integrity, and Inclusion. We weave AI into the fabric of everything we do and use it to augment the impact every individual can have. If you are passionate about solving real-world problems and ideating beside the best and the brightest, we invite you to join us! We believe collaboration thrives in person. That’s why most of our teams work from the office full time, with flexibility when it’s needed. This model supports real-time problem-solving, stronger relationships, and the kind of precision that drives great outcomes. Job Summary Shape the future of AI-powered software engineering at Palo Alto Networks. As part of our AI Transformation group, you’ll join a multidisciplinary group building state-of-the-art, agentic AI systems that directly elevate the productivity of thousands of internal engineers. We build internal AI infrastructure, frameworks, agents, harnesses, methodologies, and adoption programs powered by cutting-edge LLMs. Whether you are researching novel AI paradigms, architecting platform infrastructure, engineering end-to-end agentic tools, or driving developer enablement, your work will redefine how software at Palo Alto Networks gets built at scale. This is an applied AI research role, where you will be inventing new technology, bringing the latest innovations into our agentic software development practices, and responsible for co-building systems that get deployed to our entire, global Cortex engineering organization. Key Responsibilities • Stay at the forefront of AI advancements in agentic coding and integrate state-of-the-art techniques. • Build functional Proof of Concepts (PoCs) and architectural skeletons to evaluate new AI techniques before scaling. • Critically audit and challenge internal AI solutions, benchmarks, and architectures to prevent technological obsolescence. • Design rigorous testing methodologies to assess model accuracy, latency, cost efficiency, and drift across solutions. • Research and design advanced knowledge-retrieval architectures, including standard and graph-based RAG and hybrid contextual search. • Collaborate with core AI engineering to transition validated prototypes into reusable components for our engineering workforce. • Coordinate closely with the US Foundational AI Research team via flexible evening Israel / morning US meetings. Qualifications Required Qualifications • Minimum of 5 years of experience in Applied AI research, Data Science, or Machine Learning engineering. • Deep, hands-on experience over the past 12+ months developing leading-edge agentic coding practices. • Proficiency in Python and/or Typescript, with deep familiarity in Agentic AI orchestration libraries like LangChain, LlamaIndex, or LangGraph. • Experience with automated statistical evaluation to track model drift, latency, costs, and hallucination rates. • Hands-on experience developing advanced RAG pipelines, GraphRAG frameworks, and interacting with Graph Databases or vector indices. • Practical experience with autonomous agent protocols, multi-agent communication layers, or Model Context Protocol (MCP). Preferred Qualifications • Understanding of secure data pipelines, including Role-Based Access Control (RBAC) and prompt injection mitigation. • Hands-on production experience utilizing Google Cloud Platform (GCP) services and infrastructure. • Strong knowledge of data privacy and security considerations specific to AI and ML systems. • Post-graduate work or equivalent advanced degree in Artificial Intelligence, Data Science, or a related field. Our Commitment We’re trailblazers that dream big, take risks, and challenge cybersecurity’s status quo. It’s simple: we can’t accomplish our mission without diverse teams innovating, together. We are committed to providing reasonable accommodations for all qualified individuals with a disability. If you require assistance or accommodation due to a disability or special need, please contact us at [email protected]. Palo Alto Networks is an equal opportunity employer. We celebrate diversity in our workplace, and all qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or other legally protected characteristics. All your information will be kept confidential according to EEO guidelines. Is role eligible for Immigration Sponsorship? No. Please note that we will not sponsor applicants for work visas for this position.