לוח משרות דרושים NLP/Machine Learning בתל אביב יפו

Were looking for an Applied Data Scientist to join one of our product squads. Youll design, build, and deploy data-driven solutions that combine machine learning, statistical methods, and SQL/rules-based decision logic to power autonomous supply chain intelligence platform. Youll work closely with data science, engineering, product, and supply chain experts and own solutions end-to-end-from problem definition to production monitoring and iteration.
Responsibilities:
Deliver data science solutions end-to-end within a product squad: problem framing → data prep/labeling → modeling → deployment support → monitoring → iteration
Build, train, and improve ML models for supply chain use cases (e.g., inventory risk prediction, demand anomalies, root-cause analysis)
Define success metrics and evaluation plans with support from senior DS/PM; run error analysis and document learnings
Work with stakeholders to create and maintain ground truth (label definitions, labeling workflows, QA checks, feedback loops)
Implement hybrid decision logic by combining ML outputs with statistical methods and SQL/rules-based logic for robustness and explainability
Analyze large, multi-source operational datasets to identify trends, anomalies, and drivers of performance
Collaborate with software engineers to productionize solutions (batch and/or real-time), including testing, logging, and basic monitoring
Monitor deployed models/rules, investigate performance issues (data quality, drift, edge cases), and iterate based on outcomes
Contribute to team practices: reproducible notebooks/code, documentation, and experiment tracking

As a Machine Learning Engineer, youll work on cutting-edge
code-focused LLMs and AI agent systems
that power our companys next-generation developer platform. Youll be at the center of research, model training, and productionization of intelligent systems that understand software deeply, collaborate with developers, and help automate engineering workflows end-to-end. Your work will immediately impact millions of engineers worldwide.
Responsibilities:
Push LLM Innovation: Research, design, and fine-tune domain-specific LLMs for code generation, refactoring, debugging, and multi-turn reasoning.
Agent-Oriented Development: Build multi-agent coding systems that integrate retrieval-augmented generation (RAG), code execution, testing, and tool use to create autonomous, context-aware coding workflows.
Production-Grade AI: Own the training-to-inference pipeline for large code models-optimize inference with quantization, distillation, and caching techniques.
Rapid Experimentation: Prototype and validate ideas quickly; leverage reinforcement learning, human feedback, and synthetic data generation to push accuracy and reasoning.
Cross-Functional Collaboration: Partner with product, engineering, and design teams to ship AI-powered features that help developers focus on high-impact work.
Scale the Platform: Contribute to distributed training, scalable serving systems, and GPU/TPU-efficient architectures for ultra-low-latency developer tools.

As a Senior Data Scientist on our Applied AI team, you will join our Tel Aviv office and play a hands-on, end-to-end role in delivering innovative capabilities that help mayors and other city leaders understand their communities and improve the lives of millions worldwide. Reporting to the Applied AI Team Lead, you will collaborate with product, engineering, and fellow data-science teammates to turn cutting-edge research into production-ready solutions-quickly, reliably, and with maximum real-world impact. Youll work with a rich mix of data sources (including social media, news stories, survey results, resident feedback, and more) to create models and AI-powered features that scale.

Day to Day

Design, build, and deploy AI and machine-learning solutions, from data exploration through modeling, evaluation, and integration into customer-facing products and internal tools.
Optimize models for quality and scalability through feature engineering, hyper-parameter tuning, runtime profiling, and thoughtful architectural choices.
Build and maintain data pipelines using tools such as Airflow, Spark, and Databricks to ensure clean, reliable inputs for downstream models.
Collaborate closely with product managers, engineers, and designers to refine problem statements, iterate rapidly, and ship impactful features on schedule.
Champion technical excellence by conducting code reviews, sharing best practices, and mentoring teammates across data science and engineering.
Stay current with the latest developments in AI-including LLMs, RAG systems, and AI agents-and proactively propose ways to incorporate new techniques into our workflows.
Work an in-person or hybrid schedule, spending at least three days per week in our Tel Aviv office.

we are looking for a AI/ML/Software Engineer.
Here, you will tackle ever-evolving challenges and leverage the dynamic AI landscape to craft solutions that transform the cybersecurity industry. You'll have the chance to build cutting-edge models and AI systems for cybersecurity. You'll gain deep expertise in the fields of both AI and security, engaging with all facets of Generative AI techniques and their deployment in production environments. You will collaborate with a talented team of researchers, engineers and security experts, and play a pivotal role in developing groundbreaking AI solutions. Shape the future of AI for Security with us and make an enduring impact on AI adoption across the world!
Develop and train cutting-edge AI models for the security domain.
Develop a platform for AI data processing, training, fine tuning, evaluation and other AI related needs.
Develop agentic systems that automate and uplift security operations.
Author blog posts, white papers and research papers related to developments in AI for the security landscape.
Collaborate with cross-functional teams of researchers and engineers to translate research ideas into products.
Contribute to our groups culture as an early member of the team.

We are looking for researchers and applied scientists to join the Central Applied Science team. Central Applied Science is an interdisciplinary team of quantitative scientists that aims to deliver research and innovation that fundamentally contribute to Meta's success. By applying your expertise in quantitative methods, you will be empowered to drive impact across a range of products, infrastructure and company operations.
Individuals in this role are expected to have expertise and publications within research areas in the board field of machine learning. The ideal candidate will have a passion for building data-driven products and forming research frameworks to solve challenging, real-world problems.
Research Scientist, Central Applied Science Responsibilities
Work with vast amounts of data, generate research questions that push the state-of-the-art, and build data-driven products
Develop novel quantitative methods on top of Meta's unparalleled data infrastructure
Learn new tools, systems, and programming languages quickly as required by the particular project you are working on
Work towards long-term ambitious research goals, while identifying intermediate milestones
Communicate best practices in quantitative analysis to partners
Work both independently and collaboratively with other scientists, engineers, UX researchers, and product managers to accomplish complex tasks that deliver demonstrable value
Publish research results in top-tier conferences and at leading journals
Actively identify new opportunities within Meta's long term roadmap for applied science contributions.

The financial risk management (FRM) machine learning principal will be the most senior machine learning engineer and strategist for financial risk at Meta. The principal will enable the risk organization to deliver significant lift over current long range objectives for friction and leakage through the generation of new Machine Learning opportunities for the organization and support of successful delivery of the risk management ML architecture. This person will partner closely with the FRM engineering leader (Director level) and be part of Metas risk management leadership circle.
Software Engineer, ML (Technical Leadership) Responsibilities
Address core business and technical machine learning opportunities: elevate the existing portfolio of machine learning solutions to be state-of-the-art for minimizing Metas financial losses (due to leakage, good revenues loss and friction). Following are a few examples of technical and business problems we aim to address. - Provide a solution for optimizing the risk machine learning model ensemble (covering the entire end-to-end advertiser funnel including detection, decisioning, enforcement and remediation) through optimization of the current model portfolio and individual models. - Minimize the impact of the prolonged financial fraud feedback loop. - Improve models measurement and performance. - Optimize data/label strategy. - Optimize balance between specific targeted model strategy and broad umbrella model strategy to optimize for short and long term benefits
Lead Research and Introduction of Advanced Technologies: - Collaborate with Financial Integrity's senior ML Engineers to lead the research and introduction of deep learning and Large Language Model (LLM) technologies. - Remain current on industry-wide advancements in ML and introduce relevant advancements in Financial Risk Management
Collaborate on Next-Generation ML Architecture: - Work closely with financial harms principals and risk management tech leads to deliver the next-generation ML architecture for Meta's risk management system. - Collaborate with Principal ML engineers from across the company to adopt best industry and Meta practices within the FRM team. - Resolve or mitigate design dilemmas, balancing business and technical trade-offs. - Identify and initiate opportunities for collaboration and impact with other organizations at Meta
Identify and Initiate New Business Opportunities: - Collaborate with Meta FinTech, Central Integrity and Core Ads Growth partnerships to identify and initiate new business opportunities based on third-party capabilities. - Conduct proof of concept for different opportunities and initiate integrations to enhance business performance
Grow Other Senior ML Engineers - Actively invest in the growth of other senior ML engineers through goal-driven formal and informal mentorship. Provide regular feedback to other engineers regarding their technical work.

We are building the Windows agent that powers GenAI Protect, flagship initiative to secure AI workflows across endpoints, browsers, and SaaS. In this role you will help define how AI and security intersect at the OS level and solve problems no one has solved before. If you want to work on technology that sits on the critical path of how people and machines use GenAI every day, this is where you want to be.



Key Responsibilities
Own the Windows protection layer: design and implement the core proxy, hooks, and anti-tampering mechanisms for GenAI agents.
Collaborate with Mac, Cloud, and Security Engine teams to build unified multi-platform behavior analysis.
Design IDE and developer environment integrations to monitor and protect AI-driven code flows.
Deliver production-ready, high-performance agent components with deep OS-level visibility.
Influence architecture decisions, threat models, and agent-core evolution.

We are looking for a strong, hands-on Data Scientist with knowledge in Security Research to join a cutting-edge AI and cyber security initiative .
In this role, youll be part of a growing data science team working on advanced prevention technologies, leveraging vast amounts of data and state-of-the-art machine learning techniques to help protect users on a global scale.
This is a unique opportunity to join a high-impact, research-driven environment, where you will have the chance to shape core components of a next-generation security solution.

Key Responsibilities
Research and develop innovative AI-powered capabilities for cyber threat prevention.
Perform hands-on malware analysis in Windows environments, focusing on files and related threats.
Rapidly prototype and iterate based on data insights and user feedback.
Design and build data-driven solutions with a strong emphasis on practical impact and performance.
Collaborate closely with cyber researchers, analysts, and engineers to deliver production-grade machine learning models.
Work across organizational boundaries to bring solutions from concept to large-scale deployment, considering system constraints and integration challenges.

Our algorithms team is responsible for all of the deep learning and computer vision challenges the company is facing, tackling complex real-world problems that directly affect the companys success. Youd be joining a team of experienced researchers leading the research and implementation of our algorithmic engine analyzing large streams of visual data from construction sites, together with 3D models.



What you'll do:

Research and design deep learning solutions for different computer vision problems, using tremendous amounts of visual and 3D data to meet unmatched accuracy and reliability demands.
Own the complete research cycle, from requirements to design, implementation, and benchmarking, producing innovative solutions for core company problems.
Be part of a vibrant team of bright and experienced engineers bringing the construction industry into the digital age.

Data-driven insights. Help identify new products and opportunities for the company in diverse domains.
Develop Machine Learning models. Define requirements & combine data from a wide set of sources to develop ML/DL models that will automate and speed up our business processes.
End to end model management. Conduct in depth research, POC, write production-grade code and implement it (all the way to production) using our MLOps Infra to solve a diversity of business problems

We are seeking a Product Manager for AI Platform, to lead most critical evolution: the transformation to an Agentic Platform.

This role operates as a "Startup within a Startup." You will own the end-to-end AI domain, from building the underlying technical infrastructure to launching the interfaces our customers interact with.

You will drive the entire product lifecycle: bringing innovative ideas to the table, executing on early versions, and collaborating closely with internal teams and design partners to validate value. Your ultimate goal is to mature these capabilities from early concepts into core platform standards, driving mass adoption across our entire user base.

You will serve as the knowledge center for the organization, guiding how the entire platform must evolve to support the next generation of autonomous engineering.

What You Will Be Doing

Lead AI product domain from ideation to launch of customer-facing AI interfaces and agents
Design and manage AI Agents platform, enabling customers to create, manage, and run AI agents
Drive ecosystem initiatives to make the platform native to agents through API improvements, MCP integration, and agent-accessible protocols
Define strategic direction for making "AI-Native," guiding data architecture for effective AI agent interaction
Own product roadmap and prioritization, balancing immediate needs with long-term Agentic architecture investments
Advocate across product and R&D teams to integrate AI-native interfaces and drive AI-first development mindset
Identify high-impact opportunities through customer discovery and experimentation with cutting-edge AI technologies
Collaborate with engineering and design to translate AI capabilities into intuitive, trust-building user experiences
Analyze adoption metrics and feedback to optimize AI performance and increase trust in autonomous workflows
Act as company AI center of excellence, enabling Sales, Marketing, and CS teams to articulate Agentic Engineering value

Required Data Science Engineer
About the Team
Our team focuses on delivering cutting-edge, AI-powered automated application security features within our ASPM product. We are a dynamic, agile team emphasizing seamless transitions from design to production, deployment, and ongoing monitoring. We excel at operationalizing machine learning, data science, and AI solutions into robust, secure, and high-performance security capabilities.
What You Will Do
Be a core member of a cross-functional AI innovation team, collaborating closely with software engineers, MLOps specialists, and analysts.
Design, build, and optimize end-to-end AI-driven features - from experimentation and model training to validation and deployment.
Develop production-grade code (Python and C#) to integrate advanced models and data-driven capabilities into our core products.
Continuously evaluate model performance and data quality in real-world settings, proactively driving improvements, retraining, and robust monitoring.

our company has been at the forefront of the deep learning revolution, pioneering innovations that have transformed the entire field. As the leading provider of GPUs and AI computing platforms, our company has empowered researchers and engineers worldwide to accelerate breakthroughs in artificial intelligence.
We seek a versatile Senior Software Engineer who is passionate about performance optimization and generative AI. Our team builds software solutions that enable efficient inference on the latest and greatest generative AI models. We tackle problems on all levels of the stack-from server-level request batching to GPU kernel fusion-and collaborate with teams across diverse disciplines to push our company's hardware to its full potential.
What youll be doing:
Cooperate with research teams to onboard new LLMs and VLMs into our company's opensource AI runtimes
Optimize inference workloads using sophisticated profiling and simulation tools
Build SOLID, extendable inference software systems, and refine robust APIs
Implement and debug low-level GPU code to harness the latest HW features
Own end-to-end inference acceleration features and work with teams around the world to deliver production-grade products.

we are seeking a senior NLP Data Scientist to lead our marketing language predictive modeling. Youll explore complex datasets, build and fine-tune advanced NLP/LLM models, and partner closely with engineering and product to integrate your work into AI content platform.
Responsibilities:
Define and own the technical strategy and roadmap for marketing language predictive modeling
Analyze, process, and derive insights from our ever-growing data resources
Solve challenging prediction problems by applying the latest ML/NLP techniques to build and fine-tune highly performant LLMs
Collaborate with engineers and product managers to ship models end-to-end, from research to production
Monitor and iterate on models using offline and online metrics

We are seeking a visionary Director of Algorithm to join our leadership team and report to the VP of R&D. This is a high-impact strategic role for a leader who combines deep expertise in machine learning and advanced AI with a proven track record of turning innovation into measurable business results.

As Director of AI, you will lead and expand a group of algorithm engineers embedded in Product pods, play a pivotal role in roadmap planning, and balance cutting-edge research with practical productization. You will drive cross-organizational initiatives that elevate our products and operations, defend our competitive moat, and unlock new opportunities for growth and innovation.

Key Responsibilities

Team & Talent Leadership

Manage, mentor, and inspire a team of algorithm engineers, fostering technical excellence and career growth.
Scale the AI team through hiring, skill development, and cultivating a strong data science culture.
Promote cross-functional collaboration, execution, knowledge sharing, and experimentation.
Attract senior AI talent to build strong teams.
AI Roadmap & Innovation

Execute the AI roadmap, aligned with the company strategy and product vision.
Introduce state-of-the-art techniques to solve complex challenges.
Drive initiatives that push the boundaries of whats possible, turning AI into a measurable business differentiator.
Technical Leadership

Personally led the resolution of the most complex AI/ML challenges.
Architect and guide the implementation of production-ready ML systems, ensuring robustness, accuracy, and low latency.
Maintain a strong applied research perspective while delivering practical, business-impacting solutions.

Defending & Expanding Our Moat

Keep us ahead of industry shifts by monitoring emerging technologies and evaluating competitive threats.
Build defensible AI assets - unique data pipelines, proprietary models, domain-specific enhancements - that are hard to replicate.
Shape intellectual property (publications, patents, methodologies) that strengthens our positioning.