לוח משרות דרושים NLP/Machine Learning משרה מלאה, לחיפוש זה נמצאו 111 משרות

Were looking for talented Senior Algorithm Engineer to help us develop innovative technologies for cancer diagnosis.
In this role, youll work on huge, unique datasets of high-resolution pathology images from leading institutes worldwide, develop and optimize algorithmic solutions for complex problems using cutting-edge technology, integrate your algorithms into our products and receive feedback from clinicians using them in live clinical settings, and work closely with our multi-disciplinary team of Machine Learning experts, experienced software developers and medical professionals.

We are seeking a highly motivated and talented Junior AI Scientist to join our FILM (Foundation Intelligence & Learning Models) team. This role is designed for an early-career professional or a recent graduate who is passionate about driving customer impact, through the frontier of Artificial Intelligence, Generative AI and agentic architecture. As a Junior AI Scientist, you will work closely with senior researchers and engineers to develop, refine, and deploy cutting-edge AI solutions that impact our core technology stack.
Responsibilities:
Assist in the research and development of Generative AI (GenAI) applications and frameworks.
Clean, analyze, and interpret large datasets to derive actionable insights for model training and evaluation.
Participate in the full lifecycle of GenAI development, from initial concept to deployment and monitoring.
Stay up-to-date with the latest advancements in GenAI/ML research and propose innovative ideas to solve complex problems.

We are looking for a Senior Data Scientist to lead strategic research initiatives . This individual will be at the forefront of research, working hands-on to advance our models while also mentoring and collaborating with data scientists across the department.
Responsibilities:
Spearhead strategic research of new cutting edge Machine Learning models
Mentor and advise data scientists.
Design solutions for the companys core mission using Data Science methodologies from various domains
Work in a short life-cycle research and development environment
Generate and test working hypotheses in unexplored territory

we are looking for a AI Senior Software Engineer, ML Platform.
This is a Senior AI Software Engineer role within AI Engineering group, focused on building and scaling the infrastructure behind advanced AI solutions in computer vision and NLP for medical imaging. The role combines hands-on software development, technical leadership, and close collaboration with cross-functional teams to transform AI innovation into scalable, high-impact products.
Responsibilities:
Design, develop and lead SW development of infrastructure for innovative AI algorithms for computer vision and NLP in the context of medical imaging.
Collaborate with cross-functional teams, including researchers and product managers, to drive the development of new AI products and features.
Work in a unique professional culture applying the full range of software engineering capabilities in the core parts of the A.I. systems
Develop and maintain high-quality, scalable, and efficient code.
Take initiative in exploring and adopting of new technological advances in all relevant domains (for example, scalable cloud based systems, DL and CV SW frameworks, Large scale ML systems)

we are looking for a AI Software Tech Lead, ML Platform.
This is an AI Software Tech Lead role within AI Engineering group - working side by side with Algo teams to build and evolve AI solutions that deliver real clinical impact. Youll take ownership of the design and development of AI-driven systems, leading projects that turn advanced models into scalable, reliable components within platform. The role is highly hands-on and combines technical excellence with leadership - guiding design decisions, mentoring engineers, and collaborating across Algo, Product, and Engineering to ensure alignment, robustness, and impact.
Responsibilities:
Build and evolve the AI-specific infrastructure and components that enable robust, scalable model training and serving, working side by side with Algo teams to co-design interfaces, workflows, and deployment strategies
Stay deeply hands-on, driving complex technical work while setting high standards for design, code quality, and execution
Own project-level architecture and key technical decisions, ensuring sound design choices and smooth collaboration across teams
Promote engineering excellence and mentorship, fostering maintainable systems, clean code practices, and continuous learning
Communicate clearly and proactively throughout design and development-articulating goals, progress, and technical decisions to all relevant stakeholders
Collaborate across Algo, Product, and Engineering to ensure technical alignment, clear interfaces, and cohesive delivery
Continuously evaluate and adopt new tools or frameworks-from cloud infrastructure to orchestration and MLOps practices-that improve efficiency and long-term scalability.

We are looking for an experienced Applied AI/ML Scientist with expertise in building agentic systems and autonomous agents to join one of our R&D. You will be at the core of transforming our supply chain solutions into a fully agentic platform, designing and building agents that autonomously generate analytical pipelines, orchestrate multi-step reasoning, and resolve complex logistics challenges for our customers.
You will combine strong machine learning and deep learning expertise with the ability to architect and implement production-grade agentic systems, working closely with engineering, product, and domain experts to push the boundaries of what autonomous AI can do in supply chain.
Responsibilities:
Design and build autonomous agentic systems that generate, configure, and execute analytical pipelines to solve supply chain challenges end-to-end
Architect multi-agent workflows with planning, tool use, memory, and feedback loops, enabling agents to reason, adapt, and improve over time
Develop and integrate ML and deep learning models (e.g., predictive models, anomaly detection, demand forecasting) as core capabilities within agentic pipelines
Research and apply state-of-the-art techniques in agentic AI, LLM orchestration, and multi-agent systems to production use cases
Translate complex logistics and supply chain challenges into agent-based problem formulations, collaborating closely with product and domain experts
Define and implement rigorous evaluation frameworks for agent performance: correctness, reliability, robustness, and edge-case handling
Collaborate with software engineers to productize agentic solutions - including testing, monitoring, versioning, and iterative improvement
Contribute to team practices: reproducible code, experiment tracking, documentation, and knowledge sharing

Required Staff Machine Learning Engineer
Job Description Summary
The Staff Machine Learning Engineer is a senior technical leader responsible for designing, developing, and deploying production-grade AI systems for our imaging products. This role focuses on vision-language models, diffusion models, and multimodal learning, working closely with data scientists, software engineers, product leaders, and clinical experts to turn advanced AI methods into robust product capabilities.
Job Description
The Staff Machine Learning Engineer is a senior technical leader responsible for designing, developing, and deploying production-grade AI systems for our medical imaging products. This role focuses on vision-language models, diffusion models, and multimodal learning, working closely with data scientists, software engineers, product leaders, and clinical experts to turn advanced AI methods into robust product capabilities.
Key Responsibilities
Design, implement, and productionize AI models for clinical applications, including vision and diffusion models.
Own end-to-end model lifecycle: data ingestion, training, evaluation, deployment, monitoring, and iteration.
Work with large-scale medical datasets, ensuring data quality, preprocessing, and efficient pipeline management.
Drive technical decisions and tradeoffs with a focus on scalability, maintainability, and real-world constraints.
Collaborate with clinical AI scientists to translate research innovations into production-ready solutions.
Stay current with advancements in vision-language modeling, GenAI, and related AI technologies.

We are looking for an experienced Applied Data Scientist with expertise in building agentic systems and autonomous agents to join one of our R&D. You will be at the core of transforming our supply chain solutions into a fully agentic platform - designing and building agents that autonomously generate analytical pipelines, orchestrate multi-step reasoning, and resolve complex logistics challenges for our customers.
You will combine strong machine learning and deep learning expertise with the ability to architect and implement production-grade agentic systems, working closely with engineering, product, and domain experts to push the boundaries of what autonomous AI can do in supply chain.
Responsibilities:
Design and build autonomous agentic systems that generate, configure, and execute analytical pipelines to solve supply chain challenges end-to-end
Architect multi-agent workflows with planning, tool use, memory, and feedback loops - enabling agents to reason, adapt, and improve over time
Develop and integrate ML and deep learning models (e.g., predictive models, anomaly detection, demand forecasting) as core capabilities within agentic pipelines
Research and apply state-of-the-art techniques in agentic AI, LLM orchestration, and multi-agent systems to production use cases
Translate complex logistics and supply chain challenges into agent-based problem formulations, collaborating closely with product and domain experts
Define and implement rigorous evaluation frameworks for agent performance: correctness, reliability, robustness, and edge-case handling
Collaborate with software engineers to productionize agentic solutions - including testing, monitoring, versioning, and iterative improvement
Contribute to team practices: reproducible code, experiment tracking, documentation, and knowledge sharing

we are looking for a Senior Machine Learning Engineer.
As a Senior Machine Learning Engineer , you will play a crucial role in developing and implementing machine learning models that drive our products and user experiences. You will have a significant impact on our large and growing user base by leveraging the latest AI technologies to solve challenging problems at scale. This is a unique opportunity to join a forward-thinking team that is passionate about innovation, data, and machine learning.
What youll do:
Design, develop, and deploy machine learning models for various business needs.
Collaborate with cross-functional teams, product managers, and software engineers, to integrate ML solutions into production systems.
Experiment with and iterate on model architectures to improve accuracy, efficiency, and scalability.
Work with large datasets to preprocess, clean, and extract meaningful features for model training.
Utilize MLOps best practices to automate and streamline the development lifecycle of ML models.
Monitor model performance and fine-tune for optimization.
Stay updated with the latest research and advancements in machine learning and AI.

We're looking for an experienced and passionate ML Engineering Team Lead to lead our ML Engineering team and shape the next generation of our AI infrastructure. This is a hands-on leadership role where you'll combine technical leadership, software architecture, and people management to build scalable, production-ready AI systems running on edge devices.
About The Role:
Lead, mentor, recruit, and grow a team of software engineers, fostering a culture of ownership, collaboration, and continuous improvement.
Own the team's technical roadmap, architecture, execution, and project prioritization, aligning delivery with business goals.
Design, build, and maintain scalable software and ML infrastructure across cloud and edge environments.
Partner with AI Researchers to productionize Computer Vision and Deep Learning models into reliable, high-performance systems.
Design and optimize inference pipelines with a focus on scalability, latency, and reliability.
Drive engineering excellence through architecture reviews, code reviews, development best practices, and modern AI-assisted engineering workflows.

Required Data Engineering Manager
Data, Ramat Gan, Israel (Hybrid)
Description
We are one of the most popular and downloaded apps in the world. Working with us provides a unique opportunity to influence hundreds of millions of our users and to be part of the journey that makes us a super-app. Our mission is to make peoples lives easier by enabling meaningful connections, from precious moments with family and friends, through managing business relationships to pursuing their passions.
As an Engineering Manager in the data department, youll build and scale our data platform and data apps that powers our business insights. Youll design and implement robust pipelines to process billions of daily records, leveraging cutting-edge cloud technologies to transform data into actionable intelligence.
If youre passionate about data engineering and driving business growth through insights, wed love to hear from you!
Responsibilities
Lead and grow Data Engineering and Machine Learning teams in a high-scale environment (tens of billions of events per day).
Own the design and evolution of a self-service data platform enabling internal teams to easily build, ship, and consume data products.
Architect and scale batch and streaming pipelines powering core business and ML use cases.
Drive production ML systems end-to-end (recommendation, ranking, prediction) with direct business KPI impact.
Ensure reliability, scalability, and observability of large-scale data and ML systems in production.

We are looking for an experienced NLP Data Science Team Leader to lead a team of talented NLP Data Scientists and drive the development of cutting-edge NLP solutions at scale. This role combines hands-on technical leadership, people management, and strategic influence over product and research directions.
Responsibilities:
Lead and grow a team of NLP Data Scientists
Manage, mentor, and support team members professional development
Foster a culture of excellence, ownership, and continuous learning
Own end-to-end delivery of NLP solutions
Oversee algorithmic features from ideation through research, development, and production
Ensure high-quality, scalable, and maintainable solutions
Drive technical direction and innovation
Guide research efforts and evaluate new NLP/ML technologies
Translate business needs into impactful NLP solutions
Collaborate cross-functionally
Work closely with Product, Engineering, and Business stakeholders
Align team priorities with company goals and product roadmap
Maintain hands-on involvement
Contribute to architecture, modeling, and critical algorithmic challenges
Review code, experiments, and methodologies

Required Staff ML Engineer
Tel Aviv
As a Staff ML Engineer, you will play a central role in shaping how millions of riders and drivers move through our cities every day. Our team sits at the intersection of machine learning, optimization, and real-world operations - turning complex, multi-dimensional challenges into the real-time intelligence that powers our mass-scale automated dispatch system. This is a rare opportunity to work on problems that are genuinely hard, at a scale that is genuinely rare, where the solutions you build have a direct and visible impact on the efficiency and reliability of transit networks around the world.
About the Role:
Own the development of ML models and optimization algorithms that drive our real-time dispatch system - making smart, scalable decisions across thousands of simultaneous rides, drivers, and operational constraints.
Design and implement online algorithms for real-time decision-making, balancing system utilization with a consistently high quality of service for riders - where every millisecond and every percentage point of efficiency matters.
Model and mathematically represent competing demands on our system, translating messy real-world operational complexity into elegant, tractable formulations that can be solved at scale.
Use sophisticated statistical methods to analyse demand patterns, traffic dynamics, and fleet performance - generating insights that directly inform algorithm development and operational strategy.
Collaborate closely with engineering, product, and operations teams to bring complex algorithmic work to life in production - owning the full journey from research and prototyping through to real-world deployment and iteration.