Machine Learning Engineer jobs in Tel Aviv-Yafo

Join Ovalix and Help Secure the AI Era We're building the platform that gives enterprises visibility, governance, and protection across their AI ecosystem, from public GenAI tools and homegrown apps to coding assistants and autonomous AI agents. We're looking for people who want to solve real enterprise AI security challenges and move fast with a friendly, focused team. Responsibilities ML is the heart of our product: detecting and classifying risks in real-world AI traffic with NLP and LLMs. You'll own models from research to production and shape our ML direction from day one. Requirements 5+ years of hands-on DS/ML experience in Python, taking models from research to production. Strong NLP background and hands-on experience with LLMs (prompting, fine-tuning, evaluation). Solid engineering skills — comfortable owning data pipelines and inference services in production.

Description About Tenzai Tenzai is building autonomous AI hackers that think like the world's best offensive security experts, act like them, and then help fix what they find before the real ones do. If this mission speaks to you, come defend the world's software: autonomously, continuously, and in-depth. About the role This is a rare opportunity to work at the intersection of offensive security and AI — and to have your expertise shape a platform used at enterprise scale. Your work will be deployed and used to hack into applications and systems in the real world. Responsibilites • Design and implement reinforcement learning workflows to train state- of- the- art LLMs specializing in cybersecurity. Design tasks, datasets, and benchmarks for training and evaluating LLMs and agents. • Work on experimentation and evaluation systems — evals are key to everything we do. In this role, you will build evaluation pipelines, design and build experiments, and construct simulations. Requirements • Strong understanding of modern LLMs, including training, post-training, RL, fine-tuning, and inference, with hands-on experience deploying LLM-based systems in production. • Hands-on experience building an agent, including working with complex loops, context engineering, and long-execution tooling. • 5+ years of hands-on programming experience in Python or other backend languages. Strong fundamentals in system design, performance, and debugging. • Experience with data systems and data modeling (databases, pipelines, etc.). • Real-world experience running experiments, measuring outcomes, and iterating. Bonus points • Advanced degree or research experience. • Good understanding of modern, AI-driven software development. Why Tenzai • Working on problems that matter - Software is now written and deployed faster than it can be secured. Attackers are beginning to use AI to find vulnerabilities at scale. Tenzai exists to close that gap. It's a mission that requires elite hackers, and also sharp storytellers, wicked-smart operators, and experienced market builders. • Building a category in the making - Tenzai is defining a new category in cybersecurity. That means every team — from research and engineering to product, brand, and go-to-market — has a chance to shape how the industry understands and adopts autonomous security. If you thrive building something from zero and helping a new idea take hold in the world, keep reading. • Talent density - We believe small teams of exceptional people outperform large organizations. Tenzai was founded by veteran security experts and repeat entrepreneurs. We hire deliberately and value curiosity, initiative, and craftsmanship, whatever your discipline. • Creating real impact, quickly - Whether you're building systems, shaping product experiences, telling the story, or helping customers succeed, your work will immediately influence how organizations secure their software. We move quickly, keep teams lean, and give humans ownership. • Ambition with humility - We're tackling hard problems with a team that values deep expertise and thoughtful collaboration. Everyone here is learning, experimenting, and pushing the boundaries of what's possible. Plus, we love eating lunch together.

Description We’re hiring a ML Engineer to accelerate AI-driven innovation across Stampli’s B2B SaaS platform. You’ll be at the forefront of building intelligent systems that power core product experiences and automate internal operations, driving efficiency, speed, and scale across the organization. This is a high-impact, hands-on role in a fast-growing, AI-first company where machine learning is a foundational pillar, not a bolt-on feature. You'll partner with product, engineering, and operations teams to design and implement powerful ML and LLM-based solutions that make a measurable difference. What You Will Do • Build Intelligent Systems: Design and develop ML/LLM-powered solutions that solve real-world challenges across Stampli’s product and internal workflows. • Own Full Lifecycles: Take projects from concept all the way to production, including model training, evaluation, integration, and monitoring. • Leverage State-of-the-Art Tools: Work with leading frameworks like LangChain, Hugging Face, TensorFlow, and PyTorch to deliver cutting-edge functionality. • Collaborate Cross-Functionally: Partner with product managers, engineers, and stakeholders to embed AI capabilities into user-facing features and backend services. • Ship at Scale: Build and maintain scalable APIs and services, integrating best practices in CI/CD, observability, and cloud infrastructure. • Report with Impact: Share progress, challenges, and results clearly with technical and executive stakeholders. What You Will Bring • 6+ years of experience as a Backend Developer, Data Engineer, or ML Engineer • Strong proficiency in Python • Deep expertise in designing scalable, resilient, fault-tolerant and secure backend systems • Strong experience with distributed systems, microservice patterns, asynchronous processing and event-driven architecture • Proven ability to design and operate high-throughput APIs in production • Experience leading technical design reviews and making sound architectural tradeoffs • Excellent problem-solving skills and ownership mindset • Strong collaboration and communication abilities Bonus if you have: • M.Sc. in Computer Science, Software Engineering, or similar field • Deep experience with LLMs and ML frameworks (e.g., LangChain, LangGraph, Hugging Face, TensorFlow, PyTorch) • Experience building and scaling LLM-powered applications • Familiarity with AWS and DevOps best practices (CI/CD, monitoring, IaC) • Exposure to NoSQL and real-time data processing pipelines You Will Get • AI-driven workplace: Work with cutting-edge tools like ChatGPT Enterprise to enhance productivity, spark innovation, and streamline your day-to-day. • Hybrid model: Join us in our Tel Aviv office three days a week (Tue–Thu), with the flexibility to work remotely the rest of the week. • Stock options and real ownership in what you help build. • Career growth supported by experienced, innovation-focused leadership. • Modern, inclusive environment within a fast-moving scale-up culture. Why Join Stampli? Stampli is revolutionizing financial operations with AI, far ahead of competitors. For nearly a decade, our AI assistant, Billy, has set the industry standard—processing $100B+ in invoices annually and saving millions of labor hours for 1,600+ customers. More than automation, Billy transforms finance teams by freeing them of manual work. Our explosive growth places us among the top tech companies at our stage, with exceptionally low churn. After conquering the Accounts Payable space, we're now revolutionizing the entire procure-to-pay (P2P) lifecycle with our new platform that "connects every dot from request to reconciliation." What sets us apart? We adapt to customers—not the other way around—integrating with 70+ ERPs in weeks, not months. Our customer-first approach extends to our award-winning workplace culture, with vibrant, global offices. We've earned multiple Comparably awards, including Best Company Outlook, Work-Life Balance, Compensation, Happiness, and Perks & Benefits. Here at Stampli, we build exceptional products with exceptional people. Join our dynamic team where your career will thrive in an environment that champions creativity, collaboration, and growth!

Your work days are brighter here. We’re obsessed with making hard work pay off, for our people, our customers, and the world around us. As a Fortune 500 company and a leading AI platform for managing people, money, and agents, we’re shaping the future of work so teams can reach their potential and focus on what matters most. The minute you join, you’ll feel it. Not just in the products we build, but in how we show up for each other. Our culture is rooted in integrity, empathy, and shared enthusiasm. We’re in this together, tackling big challenges with bold ideas and genuine care. We look for curious minds and courageous collaborators who bring sun-drenched optimism and drive. Whether you're building smarter solutions, supporting customers, or creating a space where everyone belongs, you’ll do meaningful work with Workmates who’ve got your back. In return, we’ll give you the trust to take risks, the tools to grow, the skills to develop and the support of a company invested in you for the long haul. So, if you want to inspire a brighter work day for everyone, including yourself, you’ve found a match in Workday, and we hope to be a match for you too. About the Team As the leading provider of Talent Orchestration technology, HiredScore’s artificial intelligence, automation and deep integrations empower the largest and most innovative companies in the world to safely and transparently drive critical business outcomes in recruitment productivity, diversity hiring, internal mobility, and total talent management. HiredScore is designed to help companies match, rediscover, and engage talent more effectively. Seamlessly integrated with Workday, it streamlines processes, reduces administrative tasks, and delivers timely insights that enhance decision-making and free up time for meaningful interactions with top talent. We place great value on career growth, learning and collaboration. Employees are our #1 value! We are an agile organization, constantly looking for ways to improve with a focus on the value we deliver to our customers. We work closely with people to acquire fast feedback and achieve the right outcomes. At our Israeli site, we follow a hybrid work model with 3 days in the office and 2 days from home About the Role • Design, build, and improve ML-powered software products that deliver real value to users. • Explore, analyze, and model large-scale textual data to support accurate predictions, classification, and decision-making. • Develop and evaluate NLP and machine learning models, using LLMs and generative AI techniques when relevant. • Move quickly from data analysis and experimentation to prototypes, production-ready code, and integration with other services. • Own the quality, performance, and ongoing improvement of your work through metrics, evaluation, and data-driven iteration. • Collaborate with product, engineering, and research partners while learning from a strong technical team. About You Basic Qualifications: • 4+ years of experience as a machine learning engineer, data scientist, software engineer or in a related technical role. • Strong Python skills, with experience building, shipping, and maintaining production-grade code. • Solid software engineering fundamentals, including clean APIs, testing, CI/CD, observability, and maintainable codebases. • Practical experience working with large-scale data, data modeling, and production systems that support data-driven products. • Familiarity with machine learning, deep learning, and NLP concepts, with hands-on experience using frameworks such as PyTorch, TensorFlow, or scikit-learn. Other Qualifications: • Bachelor’s degree in Computer Science or a related field; Master’s degree is a plus. • Experience with GenAI and LLMs. Our Approach to Flexible Work With Hybrid Work, we’re combining the best of both worlds: in-person time and remote. Our approach enables our teams to deepen connections, maintain a strong community, and do their best work. We know that flexibility can take shape in many ways, so we require employees to work three days a week in the office and two days at home. This means you'll have the freedom to create a flexible schedule that caters to your business, team, and personal needs, while being intentional to make the most of time spent together. Workday is committed to providing reasonable accommodations for qualified individuals during our application process, in order to perform one or more essential functions of their job, as well as regarding the use of AI tools for employment decision-making to any degree. Please see below for more details including how to request an accommodation as a qualified veteran, due to a disability or for religious reasons, or as otherwise provided under applicable law. Workday prohibits taking adverse action against any candidate or employee for reporting a possible violation of this policy, requesting one or more work accommodations, exercising a privacy right, or cooperating in an investigation in accordance with applicable law. Any employee who retaliates against a candidate or employee for doing so may be subject to disciplinary action, up to and including termination of employment, to the fullest extent allowable under applicable law. If you require a reasonable accommodation, you may email [email protected], as far in advance as possible. Are you being referred to one of our roles? If so, ask your connection at Workday about our Employee Referral process! At Workday, we value our candidates’ privacy and data security. Workday will never ask candidates to apply to jobs through websites that are not Workday Careers. Please be aware of sites that may ask for you to input your data in connection with a job posting that appears to be from Workday but is not. In addition, Workday will never ask candidates to pay a recruiting fee, or pay for consulting or coaching services, in order to apply for a job at Workday.

Description Kela is a defense technology startup pioneering next-generation command-and-control and data infrastructure systems. We empower defense organizations with robust, scalable, and secure platforms that integrate diverse sensors and AI to deliver real-time battlefield intelligence. Backed by leading investors, Kela combines Israeli innovation with global mission impact. Join our Algorithms Department to solve mission-critical, real-world challenges. You will sit at the forefront of national defense, developing cutting-edge algorithms and AI systems that turn raw sensor data into actionable intelligence. Responsibilities: • Research, develop, and optimize sophisticated algorithms, from classical computer vision methods to advanced deep learning models. • Build models and algorithmic pipelines for detection, classification, segmentation, and scene understanding in complex operational environments. Requirements • B.Sc. or M.Sc. in Computer Science, Machine Learning, Data Science, or a related field • A natural ability to deconstruct complex, non-standard algorithmic and mathematical challenges. • Strong grasp of deep learning, model training, optimization, and evaluation; experience in computer vision is a major advantage. • Professional experience in Python, NumPy, and PyTorch or similar frameworks. • Experience with machine learning, optimization, or probabilistic modeling is highly valued.

Description Chips Talk, We Listen proteanTecs is a game-changing startup that's giving advanced electronics the power to report on their own health. In a digital world built for autonomous driving, cloud computing, and AI, we depend on computing systems daily. But how can we guarantee their safety, reliability and functionality? proteanTecs is the first-ever company to provide visibility into next-gen chips while they are operating, based on the power of on-chip monitoring, machine learning, and data analytics. Here at proteanTecs, you'll be part of a team that's unlocking deep insights to make electronics more reliable, efficient, and high-quality. We're trusted by industry leaders in data centers, automotive, communications, and consumer devices – we work with the world's largest and most notable companies in tech. Why proteanTecs is a great place to work: • Fast-paced and impactful: We're a mission-driven startup, so you'll tackle new challenges daily, wear many hats, and see your work directly influence the future of electronics. • Supportive company culture: Learn from the best. Our 200+ team members are experts in their field with a proven track record of success, and they're committed to fostering a collaborative and supportive work environment. • International presence: We're a multinational company with a diverse team across multiple locations around the globe. You'll collaborate on projects with international impact, gaining a global perspective of the tech industry. • Work with industry leaders: Our solutions are used by the biggest names in tech. You'll be part of the team creating the next generation of groundbreaking products. • Cutting-edge playground: We use the latest machine learning, platforms, and tools to push boundaries and achieve breakthroughs. • Real-world impact: Our work keeps data centers, cars, and other critical systems running smoothly. Your work will directly contribute to safer, more reliable electronics. • We are here for the win: Backed by industry veterans and leading investors, we offer a stable and secure work environment with plenty of room for growth. We are looking for a Senior Machine Learning Algorithm Engineer who is passionate about solving complex, real-world problems at the intersection of hardware and software. Location: Tel-Aviv in hybrid model. Requirements • B.Sc. in Electrical Engineering – MUST • 5+ years experience in algorithm development, preferably in complex, data-intensive environments • Deep expertise in Python, including statistical and machine learning packages • Proven experience across all algorithm development phases: research, implementation, testing, deployment, and debugging· Familiarity with testing frameworks (e.g., unit tests, E2E tests, performance and memory profiling) • Intensive usage of AI coding tools like Cursor or equivalent (e.g., GitHub Copilot, CodeWhisperer) Advantage • M.Sc. or higher in Electrical Engineering, Computer Science, or a related field • Prior experience with: • HW/SW integration or ATE/Chip testing • Version control systems (e.g., Git) and CI/CD tools • Distributed compute frameworks (e.g., Spark, MLRun) • Containerization and cloud orchestration (e.g., Kubernetes, cloud APIs) • Business intelligence tools (e.g., Tableau or equivalent) • AI platforms and agents that interface with model training, data annotation, performance monitoring, or autonomous debugging • Familiarity with chip production or design methodologies Responsibilities • Develop advanced ML algorithms using data from proteanTecs Agents embedded in silicon. Example domains include: • Lifetime predictions • Clustering and dimensionality reduction • Parametric modeling and screening • Time-series forecasting • Lead end-to-end algorithm lifecycle: ideation → research → POC → design → implementation → validation → deployment. • Collaborate closely with cross-functional teams and directly with customers to continuously refine and enhance deployed solutions. • Drive integration of AI-enhanced tools and intelligent pipelines into ML workflows.

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 Team The ML Engineering team designs and builds the infrastructure and platforms that enable researchers and engineers to develop, evaluate, deploy, and operate ML models and LLM-based features at scale. We own the systems behind the ML lifecycle - from GPU-based training and evaluation workflows to model serving, LLM infrastructure, observability, internal SDKs, and developer tooling. Our internal platforms are used across multiple teams at Cyera, while the production services we enable power ML capabilities used across our customer base. We work closely with research, engineering, and DevOps teams, taking solutions from early ideation and design through experimentation and into reliable production systems. We value technical depth, ownership, curiosity, and a holistic approach to solving problems. About the Role We're looking for a strong and curious ML Engineer to join our team and help design, build, and operate the infrastructure behind our machine learning and LLM systems. In this role, you'll work across different parts of the ML lifecycle, from building evaluation workflows and improving CI/CD processes to operating production ML services and evolving our LLM infrastructure. You'll work closely with researchers, data scientists, backend engineers, and DevOps engineers to build infrastructure that enables ML solutions to move efficiently from research and experimentation to production. We're looking for someone with a holistic engineering mindset who enjoys understanding problems end-to-end - the business need, ML requirements, surrounding systems, and production environment - and turning them into reliable technical solutions. What You'll Do • Design and build ML workflows for model training, large-scale evaluation, batch prediction, and experimentation, enabling researchers and data scientists to iterate efficiently and reliably. • Develop ML infrastructure and developer tooling by automating recurring processes, improving CI/CD and model build flows, and creating tools that simplify ML development and operations. • Operate and improve production ML services, strengthening monitoring, observability, reliability, and performance across our ML and LLM systems. • Deploy and operate ML workloads on Kubernetes and cloud infrastructure, including GPU-based training, evaluation, and inference workloads. • Contribute to our LLM platform, including self-hosted model serving, LLM gateways, internal SDKs, evaluation and observability infrastructure, and integrations with different model providers. • Own engineering problems end-to-end, from ideation and understanding business and technical requirements through system design, implementation, deployment, and production operation. • Collaborate across research and engineering teams to build scalable infrastructure that enables ML solutions to move from experimentation into production. • Explore, evaluate, and integrate emerging technologies across ML infrastructure, LLMs, and agentic systems to continuously improve our platform and workflows. Requirements Who You Are • You have 4+ years of experience in ML engineering, software engineering, backend engineering, or a similar hands-on engineering role. • You have a B.Sc. in Computer Science, Software Engineering, or a related technical field, or equivalent significant practical experience. • You have strong Python and software engineering skills, with experience designing and building maintainable, production-quality systems. • You have hands-on experience with Kubernetes and Docker, including deploying, debugging, and operating production workloads. • You have strong experience with cloud environments such as AWS, GCP, or Azure and understand the infrastructure around running distributed production services. • You have experience with ML infrastructure and the ML lifecycle, including areas such as orchestration, model serving, evaluation, training, or production inference. • You have experience with CI/CD, observability, and production operations, and understand what it takes to make services reliable beyond simply deploying them. • You excel at solving complex problems end-to-end, independently understanding the business context, requirements, and surrounding systems and driving solutions from design through production. • You collaborate effectively across research and engineering disciplines and can communicate technical decisions clearly. • You are technically curious and proactive, with the ability to dive into unfamiliar technologies and understand how systems work under the hood. Nice-to-Haves • You have experience with GPU workloads or high-scale ML inference, including technologies such as vLLM, BentoML, Argo Workflows, Kubeflow, or similar. • You have experience with LLM platforms and infrastructure, such as LLM gateways, evaluation/observability tooling, self-hosted models, or internal LLM SDKs. • You have experience with agentic systems, including building agents, memory layers, agent evaluation, or related infrastructure. Why Join Us? At Cyera, we own what we build and how we work. Cyerans are empowered to take initiative, move quickly, and turn ideas into impact. We push boundaries by challenging the status quo, learning fast, and continuously raising the bar - for ourselves and for the industry. We elevate together by lifting each other up, celebrating wins as a team, and recognizing that our success is shared. 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 Who We Are You are looking for a role that challenges you intellectually and lets you build things that matter. You have an entrepreneurial mindset, you enjoy solving complex technical problems, and you thrive in a fast-paced startup environment. Most of all, you want your work to have meaning. We're Darrow – a fast-growing startup in the Legal Exposure Management space. We have an open, action-driven culture unlike any other. Our work starts from a simple idea: legal exposure should be visible while it's still possible to act on it. We've built a technology engine that scans massive amounts of public data to identify legal exposure and evaluate its financial value at sale, and every tool or workflow you build here moves that mission forward. We have one advantage technology and AI can't replicate: our people. More than 100 people worldwide, in Israel, US & Europe who are smart, humble, curious people who thrive at the intersection of law and AI, and we're looking for the leader who will protect and grow that edge as we scale. About the Role A Senior AI/ML Engineer role on our Data team, sitting at the intersection of AI engineering, data science, and data platform. You'll build agentic, LLM-based systems that turn vast amounts of unstructured information into high-quality structured signals — powering Darrow's products and surfacing legal risk — owning each solution across the full lifecycle, from exploration to production. You'll work closely with data engineers, data scientists, product managers, and legal experts to turn ambiguous problems into scalable AI capabilities. This is a hands-on role for someone with strong engineering judgment, deep data/ML expertise, and a focus on reliability beyond the prototype stage. What You'll Do • Design, build, deploy, and operate production AI systems: agentic, LLM-based extraction workflows and batch/online inference pipelines and owning them from exploration through deployment, monitoring, and iteration. • Define quality metrics and build evaluation datasets, testing processes, and feedback loops for ML and LLM systems; monitor accuracy, latency, cost, and data quality, and investigate and fix failures. • Explore large, complex datasets to surface useful features and patterns, and translate findings into production-grade implementations. • Partner with data engineers on ingestion, transformation, orchestration, and storage to deliver dependable data products. • Use AI-assisted coding tools (e.g., Claude) effectively while maintaining strong technical judgment and ownership of your systems. • Help shape engineering standards for production AI: testing, observability, reproducibility, data lineage, versioning, and safe deployment. Requirements What You Bring • 6+ years in ML engineering, AI engineering, data science, or backend engineering for data-intensive systems, with hands-on experience taking systems to production (deployment, monitoring, evaluation, versioning, improvement). • Strong Python skills and data orientation — SQL, NoSQL, data pipelines, and both structured and unstructured data. • Solid data science foundation: feature engineering, statistical reasoning, experiment design, error analysis, and relevant metrics (precision, recall, accuracy, coverage). • Experience with LLM-based applications: structured extraction, tool calling, agentic workflows, prompt design, embeddings, retrieval, and model evaluation. • Understanding of production AI tradeoffs, quality, latency, scalability, reliability, cost and experience integrating AI into batch, orchestration, API, or event-driven workflows. • Ability to work independently in ambiguous environments, breaking problems down and driving them to production. • Strong communication skills across engineering, data science, product, and domain-expert teams. Nice to Have • Document intelligence, information extraction, entity resolution, classification, ranking, or large-scale enrichment pipelines. • Experience building or operating agentic systems in production. • Natural Language Processing experience. • Familiarity with orchestration/ML tooling (Airflow, Dagster, Prefect, MLflow, or similar). • Experience with data warehouses, data lakes, vector databases, or modern data-processing frameworks. • Cloud-native experience: AWS, Docker, Kubernetes, IaC, CI/CD. • Experience with human-in-the-loop review or feedback-driven AI systems. • Familiarity with legal, financial, compliance, or other data-intensive domains where quality and explainability matter. What Success Looks Like • AI capabilities move reliably from experimentation to production, on systems engineers, scientists, and domain experts can depend on. • Agentic workflows deliver accurate, measurable structured data that strengthens Darrow's products and decision-making.

Machine Learning Engineer About Millennium Millennium is a global, diversified alternative investment firm, founded in 1989. Defined by evolution, innovation and focus, Millennium’s mission is to deliver results for our investors. Our people are empowered with both independence and support: the autonomy to pursue ideas with conviction and the backing of a global network committed to collaboration, disciplined risk management and continuous learning. With opportunities to deepen expertise and accelerate development, talent at Millennium is equipped to adapt, evolve and build lasting impact over time. Discover how transformative growth accelerates impact. Our Israel office is located in the Bursa area of Ramat Gan. This role is on-site. As a global firm, proficiency in English is required. Meet the Team The Information Technology department is core to the health and growth of Millennium’s business. Supporting the firm’s active, multi-manager model, the team develops flexible, scalable technology and advanced proprietary systems, including next-generation analytical, trading, and AI capabilities. Based on-site in Millennium’s Israel office in the Bursa area of Ramat Gan, the team builds and evolves enterprise technology platforms that enable innovation across the firm. What You'll Do • Lead the development of AI and machine learning capabilities within the infrastructure group across multiple applications. • Transform rapid prototypes into production-grade AI and machine learning systems that deliver measurable business value. • Identify repeatable patterns and technical friction points across Millennium’s AI stack, translating them into reusable capabilities such as LLM routing and dedicated-hardware inference optimization. • Design and implement scalable AI infrastructure that supports federated agent development and distributed deployment across the organization. • Orchestrate AI agents across distributed systems and service buses, ensuring generated code aligns with enterprise architecture standards and best practices. • Build high-performance evaluation pipelines and observability frameworks to assess agentic systems against rigorous accuracy, safety, and latency requirements. • Advance the adoption of AI-augmented development practices by providing technical leadership and integrating AI-powered tools into engineering workflows and CI/CD pipelines. • Partner directly with teams across the firm to teach AI infrastructure best practices and guide successful adoption. What You Bring • Bachelor’s degree with 6+ years of experience, Master’s degree with 4+ years of experience, or PhD with 2+ years of experience in Computer Science, Data Science, Machine Learning, or a related field. • Experience building or operating AI/ML infrastructure, agent orchestration platforms, or comparable AI-powered development tools. • Proficiency in Python and PyTorch or a similar deep learning framework. • Strong understanding of enterprise software architecture patterns and distributed systems design. • Production experience with Docker, Kubernetes, and container orchestration. • Strong communication and teaching skills, with the ability to partner effectively with teams across the organization as a deployed engineer. • Experience with cloud platforms such as AWS, Azure, or GCP; infrastructure-as-code tools; and MLOps practices, including model training, versioning, deployment, monitoring, drift detection, and performance optimization. • Experience building agentic AI systems using frameworks such as LangGraph, LangChain, or PydanticAI, including LLM integration, tool calling, structured outputs, MCP implementations, vector databases, embedding pipelines, and retrieval-augmented generation architectures.

DRW is a technology-driven, diversified principal trading firm. We trade our own capital at our own risk, across a broad range of asset classes, instruments and strategies, in financial markets around the world. As the markets have evolved over the past 25 years, so has DRW – maximizing opportunities to include real estate, cryptoassets and venture capital. With over 1,000 employees at our Chicago headquarters and offices around the world, we work together to solve complex problems, challenge consensus and deliver meaningful results. It’s a place of high expectations, deep curiosity and thoughtful collaboration DRW is looking for highly skilled Machine Learning Engineer for an Algorithmic Trading Research Group in Tel Aviv. DRW office is located at the TLV expo center, right next to TLV University train station and offers highly competitive compensation packages. As a Machine Learning Engineer, you will be an integral member of an algorithmic trading team comprised of experienced technologists and quantitative researchers. Your team will work closely to solve challenging technical problems and contribute to our full tech stack, from hardware and software development to grid computing. You will be surrounded by cutting edge technology, offered training and continuing education opportunities, and given immediate responsibility. We are looking for creative technologists, natural programmers, and disciplined engineers eager to develop new technologies that directly impact our business. How you will make an impact: • Build infrastructure for running Machine Learning algorithms on big data. • Optimize Machine Learning algorithms to run under latency constraints. • Parallelize Machine Learning algorithms to run on a parallel compute grid. • Build software for data acquisition and cleaning that can handle hundreds of terabytes of data. • Build data visualization tools for feature exploration and model verification. • Integrate Machine Leaning algorithms into trading strategies simulations to verify end to end performance improvements. • Contribute to technological innovation through exploration of cutting-edge hardware, software, and methods. • As an active member of the research team you will have an impact on the technological direction and the analysis of trade-offs between complexity and performance. What you bring to the team: • MSc-Bsc in Computer Science, Computer Engineering, or related field. • 5+ years of software development experience in modern C++ and Python. • A strong understanding of object-oriented design, data structures, and algorithms. • Ability to advise and collaborate with researchers on software engineering tools and practices. • A solid foundation in programming with the ability to think, communicate, and code clearly. • Skills in numerical computing, machine learning, and visual intelligence. • Demonstrated ability to produce algorithmic code in a fast-paced environment. For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at https://drw.com/privacy-notice. California residents, please review the California Privacy Notice for information about certain legal rights at https://drw.com/california-privacy-notice. #LI-GV1 #LI-Onsite

About Hello Heart: Hello Heart is on a mission to make heart attacks a thing of the past. We’re an AI company focused exclusively on heart health, building a platform that predicts and prevents cardiac events before they happen—identifying risk up to 10 days in advance versus 10 years in traditional clinical models. This is already working at scale. Hello Heart has been shown to reduce inpatient hospital days by 47% and deliver ~$1,800 in annual savings per member. Hello Heart is the cardiac prevention partner to over 80% of large U.S. health plans and serves hundreds of public and private employers. We’re defining how the #1 cause of death—heart disease—is managed in the AI era. Join us. About the Role: Hello Heart is looking for a Senior ML Engineer/ML Ops to own the engineering behind the models in the Hello Heart app: member engagement, cardiovascular risk stratification, and personalized health recommendations. You'll be the first engineer dedicated to ML on our Data Platform team, and you'll own the full model lifecycle: training pipelines, the model registry, automated evaluation and release, real-time and batch serving, monitoring, and retraining. You'll work closely with the data scientists who own the modeling and with the product engineers who call the models, so that what they build ships safely and runs reliably. Our models run on Snowflake ML. Our ML platform is still taking shape, so you'll set the standards rather than inherit them. You should have a proven record of owning ML systems in production and be comfortable using AI coding assistants as a core part of your workflow. Responsibilities: • Turn model releases into a pipeline: every new version is evaluated automatically, gated against the one in production, approved, and rolled out with a fast rollback. • Build drift and performance monitoring for our production models, and the retraining that follows from it. • Own the model lifecycle end to end: training pipelines, versioning and the model registry, automated evaluation, promotion and rollback, deployment, monitoring, and retraining. • Build CI/CD for ML: automated testing and validation of every model version, release gates with clear criteria, and an audit trail of who shipped what and why. • Serve models in real time through our Python model-serving service and Snowflake Container Services, with a focus on low latency, reliability, and graceful degradation. Run batch inference in the warehouse with clear standards for latency, correctness, and cost. • Build and operate ML pipelines in Airflow and Snowflake, from feature preparation through training and batch scoring, with reproducible training data. • Monitor drift, data quality, latency, and model performance, and automate retraining that goes through the same release gate. • Partner with data scientists, product engineers, and data engineers. Define clear interfaces between modeling, serving, and the services that consume models, and push back when a request belongs elsewhere. • Handle members' health data responsibly: access control, pseudonymization, and nothing sensitive in logs. • Write high-quality, well-tested production code, and own its observability, debugging, and reliability. Requirements: • 5+ years of software engineering, including 3+ years of hands-on MLOps owning production ML systems on AWS with a data or ML platform (e.g., Snowflake ML, Databricks, SageMaker, Vertex AI). • Hands-on model management: versioning, registries, automated evaluation, and promotion and rollback of models in production. • Experience building CI/CD and pipelines for ML: automated training, validation, and deployment (e.g., Jenkins, GitHub Actions), with orchestration in Airflow or similar. • Strong Python experience, including building and operating Python services (APIs or gateways) in production. • Experience serving models in real time: low-latency inference, autoscaling, and reliable serving architectures. • Strong SQL and data warehouse experience (Snowflake preferred). • Experience monitoring models in production (drift, data quality, and performance) and acting on what you find. • Experience owning a solution end to end, from pipeline and model integration through deployment and production debugging. • Proficiency with AI coding assistants as a core part of your workflow, and the judgment to review and verify what they produce. Nice-to-Haves: • Snowflake ML: Model Registry, Snowpark Container Services, ML Observability, or Notebooks and ML Jobs. • Shadow and canary releases for models. • Feature stores and ML lifecycle tooling (e.g., Feast, MLflow, Weights & Biases). • Model development: feature engineering, training, and evaluation with scikit-learn, XGBoost, or LightGBM. • Kubernetes and infrastructure as code (Terraform). • Event-driven systems (Kafka). • Integrating LLMs into production systems. • Observability stacks (Prometheus, Grafana, Datadog). • Experience with health or other regulated data (HIPAA). Hello Heart has a positive, diverse, and supportive culture - we look for people who are collaborative, creative, and courageous. Oh, and if you want to see some recent evidence of the fun things we do at Hello Heart, check out our Instagram page.

Description Join Noma Security and help shape the future of AI security in a fast-paced, high-impact environment. Noma is building the first comprehensive AI Security and Governance Platform, helping organizations adopt AI and LLMs with confidence and control. As AI becomes core to modern enterprises, we provide seamless visibility and protection across the entire AI lifecycle. Our team works at the intersection of AI, security, and cloud, shaping a new category in a rapidly evolving market. At Noma, you’ll have the opportunity to make a meaningful impact while working with exceptional people on technology that truly matters. We’re looking for a Senior MLOps Engineer to be a core driver in how our product empowers security teams. You will be expected to deeply understand customer needs and translate them directly into product features that deliver real value. You'll own key parts of our frontend stack, drive key architectural decisions, and turn complex security data into clear, actionable business insights. As we scale our AIDR product and expand deeper into model-driven security intelligence, we are looking for a Senior MLOps Engineer to own the infrastructure, tooling, and operational foundations that power our NLP and LLM training, evaluation, and deployment workflows. You will architect and operate the systems that enable us to train, fine-tune, deploy, and monitor models at scale making ML at Noma reliable, fast, cost-efficient, and production-ready. This is a high-visibility, high-impact role where you will partner closely with DevOps, Backend, Data, and Product to establish world-class ML infrastructure from the ground up. 🛠️ What You’ll Do • Build & Scale ML Pipelines • Design, build, and maintain pipelines for training, fine-tuning, evaluating, and deploying NLP and LLM models across GPU and CPU environments. • Establish LLM-Focused CI/CD • Implement automated CI/CD workflows for ML models, including benchmarking, testing, performance gating, and production deployment. • Optimize Runtime & Inference • Select and optimize serving frameworks for low-latency, high-throughput inference, ensuring reliability and scalability. • Own ML Infrastructure • Manage training environments, experiment tracking, model registries, artifact versioning, and distributed training systems. • Operational Excellence • Monitor and optimize production models for performance, cost efficiency, availability, and observability. ✅ Requirement for success: • 5+ years in software engineering, MLOps, or ML engineering with hands-on experience deploying ML models to production. • Strong Python fundamentals and deep understanding of transformer architectures, tokenization, and NLP frameworks (PyTorch, HuggingFace). • Proven experience deploying and scaling LLMs for real-time inference—ideally on platforms like SageMaker, Vertex AI, or similar. • Expertise in GPU optimization, distributed training, and CPU-based inference optimization. • Strong cloud and Kubernetes background (EKS/GKE/AKS, Helm, Terraform, CI/CD for ML). 🎯 Nice to Haves • Background in building or operating internal ML platforms. • Knowledge of evaluation frameworks for LLM quality, robustness, or observability. • Experience working with data-driven ML operations, cost optimization, and model observability. • Understanding of security implications in ML pipelines. • Familiarity with multi-model orchestration, vector DBs, or retrieval pipelines. 💙 Perks & Benefits • Located in a prime area with easy access to public transportation, near the Hashalom train station and the Light Rail. • A bright, spacious, dog-friendly office that makes you smile the moment you walk in 🐶 • Team bonding activities, company retreats, happy hours, and holiday gifts • Pilates classes at the office 💪🧘‍♀️ • Never hungry: Monthly lunch budget, dinners provided, and a fully stocked kitchen 🍽️ • A warm, supportive, and people-first company culture • Pension & Keren Hishtalmut (advanced training fund) • A global work environment with teams across Tel Aviv, the US, the Netherlands, and London • Options that let you share in Noma’s growth and success

Description At UVeye, we're on a mission to redefine vehicle safety and reliability on a global scale. Founded in 2016, we pioneered the world's first fully automated suite of AI-powered vehicle inspection systems, combining computer vision, machine learning, and generative AI. With over $380M in funding and strategic partnerships with Toyota, Amazon, General Motors, JLR, Volvo, and Hertz, our technology is deployed across manufacturing plants, dealerships, wholesale auctions, fleets, and seaports worldwide. Named one of Fast Company's Most Innovative Companies of 2026, our 300+ global employees are solutions-oriented, accountable, and driven by one shared goal: making roads safer for everyone. We are looking for an experienced Senior Deep Learning Engineer with proven capabilities to lead the development of state-of-the-art computer vision products from concept to production. In this role, you will be a part of a highly talented R&D team driving the core of UVeye’s inspection portfolio, while researching and implementing diverse Machine and Deep Learning algorithmic solutions to solve complex, real-world visual challenges. A day in the life and how you’ll make an impact: • Design and Development of novel, robust and efficient Machine Learning/ Deep Learning algorithms for major Vision challenges. • Create Proof of Concepts (PoC) for new products and technologies, transitioning research-grade ideas into scalable, production-ready systems. • Evaluate, benchmark, and profile different algorithms on unique, large-scale proprietary datasets, while driving data-centric AI methodologies (active learning, data curation). • Collaborate with infrastructure, MLOps, and hardware teams to define future technology, features, and optimize models for real-time inference constraints (on Edge/Cloud devices). Requirements • 4+ years of industry experience in the development, optimization, and deployment of Deep Learning Algorithms in production environments. • Hands-on industry experience working on major Vision problems in fields such as Detection, Classification, and Segmentation (experience with 3D Perception, Anomaly Detection, or Multi-View Geometry is a major advantage). • Deep theoretical understanding of modern neural network architectures (e.g., CNNs, Vision Transformers - ViTs, Diffusion, or Generative AI for Vision) • Experience with Python- Must, C/C++ - An advantage. • Experience with Major Deep Learning Frameworks (such as PyTorch, TensorFlow, etc.). • Experience working with Tracking / Identification / Image Retrieval / Anomaly Detection / Pose Estimation / OCR/Image Registration -An advantage. • Comfortable in unexplored territory, independent and self-motivated. • M.Sc./Ph.D. in Computer Science, Electrical Engineering, Data Science, or a related field – A strong advantage. • Experience with AI tools and generative AI frameworks to enhance development productivity and research workflows, such as Codex, Cursor, and Claude. Why UVeye: Pioneer Advanced Solutions: Harness cutting-edge technologies in AI, machine learning, and computer vision to revolutionize vehicle inspections. Drive Global Impact: Your innovations will play a crucial role in enhancing automotive safety and reliability, impacting lives and businesses on an international scale. Career Growth Opportunities: Participate in a journey of rapid development, surrounded by groundbreaking advancements and strategic industry partnerships.

About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D. The Product In a rapidly evolving world, trust in AI depends on AI agents being grounded in fresh, verified real-world data. Search is the foundation that makes this possible. We are building an agent-native search platform designed specifically for AI systems rather than human users. Our product provides programmatic, low-latency, and observable search APIs that AI agents use to retrieve, filter, and reason over real-world information at scale. The Role As a Senior ML Engineer focused on Search Optimization, you will work on improving the quality of our search product across the all parts of the search stack. You will work on problems such as query understanding, query reformulation and expansion, retrieval, ranking, reranking, and result selection. Your goal will be to identify where search quality is lost, develop better approaches, and turn them into measurable improvements in production. This is an applied ML and information-retrieval role combining experimentation with production impact. You will work with real-world queries, large-scale search systems, and evaluation signals to improve relevance, recall, freshness, and overall result quality. In this position, your responsibility will be to • Design, implement, and operate the retrieval system for a search vertical • Connect and tune the data pipeline, from ingestion to relevance tuning • Build knowledge-graph and entity-resolution layers: entity linking / NER, ontologies, and graph databases (Neo4j or similar) • Develop structured-extraction pipelines over messy, unstructured domain data • Reason about freshness and trust: model how confident we are in a fact and how stale it has become before we serve it • Define evaluation and quality metrics for relevance and drive measurable improvements • Collaborate with crawling, indexing, and ML teams to ensure retrieval and ranking requirements are met • Enable safe experimentation with retrieval, ranking, and extraction strategies You may be a good fit if you have: • 6+ years of software engineering experience, some of it in search / information retrieval • Strong IR fundamentals: inverted indexes, BM25/TF-IDF, query understanding, ranking, and evaluation (nDCG/MRR/recall@k) • Experience with vector & hybrid retrieval: ANN, dense+sparse fusion, embeddings models • Experience building structured extraction over messy/unstructured domain data • Fluent in Python and comfortable with systems-level performance work Strong candidates may also have experience with: • Knowledge graphs: entity resolution, entity linking / NER, graph DBs (Neo4j), ontologies / schema design • Owning relevance / ranking for a real product and improving it against IR metrics • Data quality, truth discovery, or systems that decide how much to trust a piece of information • Published work on IR, ranking, or knowledge graphs Benefits & Perks: • Competitive compensation • Career growth and learning opportunities • Flexibility and ownership • Collaborative and innovative culture • Opportunity to work on impactful AI projects • International environment and talented teams What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire. If you need accommodations during the application process, please let us know.