לוח משרות דרושים NLP/Machine Learning

We are seeking a hands-on Data Engineering Team Leader to oversee our real-time data domain and lead the evolution of our data platform as it transitions from a heavy build-out to stability, quality, and scale.

This role is responsible for maintaining, hardening, and extending our event processing infrastructure, focusing on adding targeted real-time processing capabilities to support analytics and informed decision-making, our decisions are deeply data-driven. This critical role is centered on maintaining, hardening, and extending our event processing infrastructure, with a primary focus on adding targeted real-time processing capabilities. Your work will directly support our analytics and enable informed, data-driven business decision-making based on production data. Specifically, you will be responsible for the core data component of capturing the clickstream events from the website, which is the foundational functionality for all our analytics.

Looking forward, this role will help lead the team into its next phase: improving data quality and developer experience, investing in modern table formats (Iceberg), empowering analysts and data scientists, and continuously reducing cost and operational friction.

This is a player-coach role, combining hands-on technical leadership with ownership, prioritization, and mentorship.

What You'll Do
Own the end-to-end real-time and event data domain, including ingestion, processing, and downstream consumption.

Ensure stability, correctness, and observability of existing streaming and near-real-time pipelines.
Lead the design and implementation of select real-time processing components to support analytics and decision-making use cases.
Define clear ownership, SLAs, and best practices for event data usage across the company.
Lead the teams investment in modern data infrastructure
Drive architectural decisions with a long-term view on maintainability, cost, and scalability.
Team Leadership & Execution

Lead, mentor, and support a team of data engineers; set technical standards and review designs and code.
Act as a hands-on contributor in critical areas of the system.
Own planning and prioritization, balancing new investments with platform stability and technical debt.
Promote a culture of quality, documentation, and operational excellence.
Partner with Data Analytics and Data Science teams to improve data accessibility, trust, and self-service capabilities.
Improve observability across the data platform (data quality, freshness, lineage, failures).
Explore and adopt AI-assisted development tools to improve engineering velocity and code quality.
Stay current with emerging technologies in data engineering and analytics, and evaluate their relevance to the platform.

As an Applied Data Scientist, you will research, design, and implement complex algorithms that assess and monitor AI systems, including cutting-edge LLM applications. You will work in a high-paced environment where impact is key. You will collaborate closely with our engineering and product teams to push the boundaries of what automated AI evaluation can achieve, ensuring our users get the most reliable and actionable insights possible.

As an AI Solutions Engineer, youll partner with enterprise clients to understand their challenges and architect AI-driven solutions using the platform. Youll collaborate with leading data science and ML engineering teams, working alongside experienced practitioners to ensure smooth adoption and measurable business outcomes.

Youll design and deliver proofs of concept, lead workshops, and build compelling demos showcasing the capabilities of for AI evaluation, monitoring, and reliability. Acting as the key interface between our product, research, and customer teams, youll help translate technical requirements into impactful AI solutions.

Required Research Intern, Video & Image Generation (PhD)
The XR Tech Research team is seeking highly motivated Research Interns to join us in advancing the next generation of video and image generation technologies. Our team is dedicated to conducting foundational, state-of-the-art research in video generation, with a strong focus on pushing the scientific and technical boundaries of generative AI to enable future immersive and interactive experiences.
As a Research Intern, you will work alongside leading experts in computer vision, generative modeling, and multimodal learning, contributing to projects at the frontier of large-scale video and image generation models. Our work not only advances the academic field but also lays the groundwork for future XR systems and applications, shaping how people will interact, create, and connect in virtual and real-world environments.
About the Team
The XR Tech Research team has a long-standing history of groundbreaking contributions to generative AI research across modalities-from images and video to 3D and beyond. We are at the forefront of advancing foundational video generation models, collaborating with world-class research groups, and driving the next wave of innovation in immersive technologies. Our work is both academically impactful and tightly connected to real-world applications, enabling breakthroughs that redefine the future of XR.
Research Intern, Video & Image Generation (PhD) Responsibilities
Conduct research on advanced topics in video and image generation, including but not limited to generative diffusion and transformer architectures, spatio-temporal modeling, and multimodal integration.
Design, implement, and evaluate novel algorithms and model architectures.
Collaborate closely with researchers and engineers across the XR-Tech group and broader FAIR/GenAI teams.
Contribute to publications in top-tier conferences and journals in AI, computer vision, and machine learning.
Present findings and share insights that help shape both ongoing research and future directions.

Required Research Scientist Intern, AI Core Machine Learning (PhD)
We are committed to advancing the field of artificial intelligence by making fundamental advances in technologies to help interact with and understand our world. We are seeking individuals passionate in areas such as deep learning, computer vision, audio and speech processing, natural language processing, machine learning, reinforcement learning, computational statistics, signal processing, information retrieval, and applied mathematics. Our interns have an opportunity to make core algorithmic advances and apply their ideas at an unprecedented scale.
Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.
Research Scientist Intern, AI Core Machine Learning (PhD) Responsibilities
Develop novel state-of-the-art machine learning algorithms and corresponding systems, leveraging various deep learning techniques.
Analyze and improve efficiency, scalability, and stability of corresponding deployed algorithms.
Perform state of the art research to advance the science and technology of Machine Learning and Artificial Intelligence.
Devise better data-driven models for information retrieval, Multi-modal fusion, generation or media understanding (CV, NLP, Speech/ Audio).
Collaborate with researchers and cross-functional partners including communicating research plans, progress, and results.
Contribute to research that can be applied to Meta product development.

We are seeking talented engineers to join our teams in building cutting-edge products that connect billions of people around the world. As a member of our team, you will have the opportunity to work on complex technical problems, build new features, and improve existing products across various platforms, including mobile devices and web applications. Our teams are constantly pushing the boundaries of user experience, and we're looking for passionate individuals who can help us advance the way people connect globally. If you're interested in joining a world-class team of engineers and researchers to work on exciting projects that have significant impact, we encourage you to apply.
Software Engineer, Machine Learning Responsibilities
Collaborate with cross-functional teams (product, design, operations, infrastructure) to build innovative application experiences
Implement custom user interfaces using latest programming techniques and technologies
Analyze and optimize code for quality, efficiency, and performance, and provide feedback to peers during code reviews
Set direction and goals for teams, lead major initiatives, provide technical guidance and mentorship to peers, and help onboard new team members
Architect efficient and scalable systems that drive complex applications
Identify and resolve performance and scalability issues, and drive large efforts to reduce technical debt
Work on a variety of coding languages and technologies
Establish ownership of components, features, or systems with expert end-to-end understanding.

We are seeking talented engineers to join our teams in building cutting-edge products that connect billions of people around the world. As a member of our team, you will have the opportunity to work on complex technical problems, build new features, and improve existing products across various platforms, including mobile devices and web applications. Our teams are constantly pushing the boundaries of user experience, and we're looking for passionate individuals who can help us advance the way people connect globally. If you're interested in joining a world-class team of industry veterans and working on exciting projects that have a significant impact, we encourage you to apply.
Software Engineer, Machine Learning Responsibilities
Collaborate with cross-functional teams (product, design, operations, infrastructure) to build innovative application experiences
Implement custom user interfaces using latest programming techniques and technologies
Develop reusable software components for interfacing with back-end platforms
Analyze and optimize code for quality, efficiency, and performance
Lead complex technical or product efforts and provide technical guidance to peers
Architect efficient and scalable systems that drive complex applications
Identify and resolve performance and scalability issues
Work on a variety of coding languages and technologies
Establish ownership of components, features, or systems with expert end-to-end understanding.

Required Software Engineer, ML (Technical Leadership)
The financial risk management (FRM) machine learning principal will be the most senior machine learning engineer and strategist for financial risk. 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 our 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 our 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 our risk management system. - Collaborate with Principal ML engineers from across the company to adopt best industry and our 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
Identify and Initiate New Business Opportunities: - Collaborate with our 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 looking for a proactive Applied ML Engineer to join our ModelOps Team. This role serves as the Technical Gatekeeper for our AI solutions, sitting at the vital crossroads of Research, Engineering, Product, and Data. You will ensure that our cutting-edge computer vision models are not just theoretically sound, but optimized for production and perfectly aligned with business needs.

The ideal candidate possesses a unique blend of system-wide vision and coding ability. You won't just monitor performance; you will define the standards for deployment, leverage internal ML infrastructure to solve complex gaps, and ensure our AI translates into flawless real-world performance. We are looking for an initiator who can bridge the gap between high-level research and production-grade execution.
Responsibilities:

Define Deployment Standards: Determine the criteria for model success, ensuring every release meets the high bar for both technical precision and business logic.
Drive Cross-Functional Orchestration: Serve as the primary technical interface between Research, Product, Engineering, and Data teams.
Optimize the System: Use your coding ability and internal ML infrastructure to creatively improve the "Recognition Factory."
Champion Performance: Proactively identify production performance gaps and improve model behavior to better serve specific client use cases.
Evolve Infrastructure: Leverage and improve internal tools to automate the model lifecycle and ensure data integrity at scale.

we are looking for an AI Engineer to lead our MLOps team and take full ownership of our machine learning infrastructure used to train, evaluate, and deploy our state-of-the-art computer vision models. In this role, you will work closely with other team leads and Product to plan and build the future of core AI platform. You will help define technical direction, make long-term architectural decisions, and translate company goals into executable plans, directly impacting ability to scale its AI capabilities and the overall success of the company.
Responsibilities

Manage and lead the MLOps team, including mentoring, professional development, and day-to-day technical guidance
Plan and own quarterly roadmaps, sprint planning, task breakdown, and execution, ensuring alignment with company and product priorities
Design, build, maintain, and evolve ML infrastructure for training, evaluation, and deployment of computer vision models
Own the end-to-end ML lifecycle in production, including experimentation workflows, training orchestration, model versioning, deployment, and monitoring
Balance delivery and technical excellence by making architectural decisions and enforcing engineering best practices
Work closely with research, data, product, and platform teams to move models reliably from research to production
Actively contribute code to critical components and review design and implementation across the team
Evaluate and introduce new technologies and tooling to improve scalability, reliability, and developer productivity

we are 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? we are 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 our company, 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.
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: Haifa \ Tel-Aviv in hybrid model.
Responsibilities
Develop advanced ML algorithms using data from our company 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.

we are 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? we are 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 our company, 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.
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: Haifa \ Tel-Aviv in hybrid model.
Responsibilities
Develop advanced ML algorithms using data from our company 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.

We are currently looking for a Senior Machine Learning Engineer to design and implement scalable and integrate machine learning solutions into production. You will work with modern technologies like Node.js, Python, Kafka, MongoDB, and OpenSearch, AirFlow, while driving architectural decisions and CI/CD best practices. This role combines backend engineering excellence with ML deployment expertise.

The Senior Machine Learning Engineer will report directly to the Director of R&D.

Your key responsibilities will include:

Architect and develop MLE services using Python, ensuring high performance, reliability, and scalability.
Collaborate with Data Science teams to productionize ML models (model serving, monitoring, retraining pipelines).
Build and maintain CI/CD pipelines for automated testing, deployment, and monitoring.
Design and implement system architecture for distributed, event-driven systems.
Integrate and optimize Kafka for real-time data streaming and event processing.
Design and manage MongoDB schemas and queries for optimal performance.
Implement and maintain OpenSearch clusters for search and analytics use cases.
Ensure security, observability, and fault tolerance across all services.
Mentor team members and contribute to engineering best practices.

As a Data Scientist, you will sit at the very core of our company. This isn't just a role about maintaining models-its about transformation. You will be the architect of a "learning machine," turning raw data into usable metrics and developing the statistical algorithms that power our business performance.

You will collaborate with Data Engineers and Product Managers to translate the "voice of the customer" into digital insights that define the industry standard.

Key Responsibilities:
Drive Actionable Insights: Analyze diverse data sources to create insights that directly fuel business growth.
Optimize Performance: Build advanced ML algorithms for bidding-utilizing classification and clustering to maximize campaign performance.
Innovate with GenAI: Leverage Generative AI techniques to query data for intelligent insights and automate decision-making.
Own the Lifecycle: Lead projects from initial exploration and Proof of Concept (POC) to scalable production environments.
Scalability & Performance: Ensure our data pipelines and ML models can handle large-scale, dynamic datasets with high efficiency.
Metric Ownership: Create and own key performance metrics that drive innovative product solutions.

We are looking for a talented and dedicated ML & Big Data Analyst who will be a part of the Core Data group.
As part of this role, you will help us process and streamline rich and complicated datasets. Will explore and validate new data sources. Be part of the data science and data engineering force creating new features for our solution.
What does the day-to-day of a ML & Big Data Analyst look like:
Apply your expertise in quantitative analysis and data mining to turn data into insights.
Conduct research and develop tools that will ensure the quality of data and algorithms.
Utilize your deep understanding of data in order to evaluate and improve novel algorithms produced by the data scientists in your team.
Partner with Big Data Engineers to establish an infrastructure to scale solutions.