לוח משרות דרושים NLP/Machine Learning בתל אביב יפו

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 modalitiesfrom 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.

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 our company product development.

our company was built to help people connect and share, and over the last decade our tools have played a critical part in changing how people around the world communicate with one another. With over a billion people using the service and more than fifty offices around the globe, a career at our company offers countless ways to make an impact in a fast growing organization. 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, 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, Code Generation (PhD) (Tel Aviv) Responsibilities
Develop novel state-of-the-art computer vision 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 our company product development.

Central Applied Science (CAS) is a research and development team, working to improve our companys products, infrastructure, and processes. We generate real-world impact through a combination of scientific rigor and methodological innovation. Our focus is on longer-term, foundational work that addresses new opportunities and challenges across the company family of apps. The work we do enhances the company family of apps that enable billions of people to communicate with each other daily. Central Applied Science is interdisciplinary, with expertise in computer science, statistics, machine learning, and economics among many other fields. This diversity of perspectives enriches our research and expands the scope and scale of projects we can address. We deliver value through collaborative projects with other groups at our company and with the academic community. In addition, we build and open-source technical products aligned with our areas of expertise. We are looking for research interns to join the Product Algorithms team in Central Applied Science. The team is an interdisciplinary team of quantitative scientists that aims to deliver research and innovation that fundamentally increase the magnitude of our companys successes. The ideal candidate will have extensive graduate training in computer science, machine learning, or related disciplines, and the passion to solve real world hard scientific problems. By applying your expertise and passion you will be empowered to drive impact across a range of products, infrastructure and operational use cases at our company. Our internships are twelve (12) to twenty-four (24) weeks long and we have various start dates throughout the year.
Research Scientist Intern, Central Applied Science (PhD) 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 our company's unparalleled data infrastructure.
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.

We are looking for an experienced, independent team player who has great data & computer science skills, a passion for data, and excellent analytical and algorithmic skills.
This role is diverse, encompassing AI/ML, data analysis, and backend engineering.
You will play a crucial role within a mission-critical team responsible for managing the heart and brain of our primary product. This involves working on core systems, such as POS underwriting models, models for merchant operations, and more.
You will participate in cutting-edge risk management systems that safeguard the loan product's financial operation, as well as operational systems, with a direct impact on its financial success.
Our AI/ML team is part of the R&D group, so you will work closely with engineers and product managers as well.
Key Responsibilities:
Research and develop statistical behaviors, study domain-specific data.
Develop state-of-the-art machine learning models end to end, including development, deployment, and continuous improvement. Both in-weight learning and in-context learning, for risk / operations related projects. This includes integrating models into production services and ensuring compliance with regulatory processes (e.g., using SHAP values for model explainability and providing evidence for production model audits).
Operate backend infrastructure for training and deploying ML models, ensuring optimal performance and reliability.
Develop and maintain Python code for translating ML model outputs into financial decisions.
Conduct analytical research on our models impact on the portfolio.
Strategize and implement changes to enhance portfolio performance.

Were looking for a highly motivated AI Developer to help design, build, and deploy intelligent agentic systems across our product ecosystem. In this role, you'll work at the intersection of machine learning, backend systems, and modern frontend technologies to deliver AI-first features that feel magical to users.

This is a hands-on, cross-functional role ideal for engineers who love building full-fledged featuresfrom data pipelines and LLM orchestration to intuitive UI experienceswith a strong product mindset.

Responsibilities:
AI Agent Design & Integration
Design and implement autonomous or semi-autonomous agents using LLMs (e.g., OpenAI, Anthropic, open-source models).
Work with prompt engineering, RAG pipelines, and tool/plugin integrations to enable agents to interact with internal and external systems.
Build scalable agent runtimes and orchestration layers (e.g., LangChain, Semantic Kernel, ReAct-based agents).
Fullstack Product Development
Own full-stack features end-to-end: from backend APIs and data models to React-based frontend interfaces.
Integrate AI/agent capabilities into customer-facing products with clean UX and measurable performance.
Collaborate closely with design, product, and data teams to bring ideas from concept to production.
Systems & Infrastructure
Build and maintain backend services and pipelines that support AI agents, including vector search, embeddings, function calling, and observability.
Optimize inference flows for performance and cost, potentially using streaming, caching, or local model inference.
Ensure systems are secure, reliable, and compliant with InfoSec standards.
Experimentation & Continuous Improvement
Rapidly prototype and iterate on new AI capabilities and user experiences.
Analyze performance and usage metrics to drive product and model improvements.
Stay up to date with the evolving AI toolchain and emerging agent architectures.

The financial risk management (FRM) machine learning principal will be the most senior machine learning engineer and strategist for financial risk at our company. 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 companys 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 companys 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 company's risk management system. - Collaborate with Principal ML engineers from across the company to adopt best industry and our company 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 our company
Identify and Initiate New Business Opportunities: - Collaborate with our company 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 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 at our company 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 our companys data and algorithms.
Utilize your deep understanding of our companys 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.

When leading companies choose our company Cloud, it's a huge win for spreading the power of cloud computing globally. Once educational institutions, government agencies, and other businesses sign on to use our company Cloud products, you come in to facilitate making their work more productive, mobile, and collaborative. You listen and deliver what is most helpful for the customer. You assist fellow sales our companys by problem-solving key technical issues for our customers. You liaise with the product marketing management and engineering teams to stay on top of industry trends and devise enhancements to our company Cloud products.
As a Customer Engineer, you will partner with technical Sales teams as a subject matter expert in Artificial Intelligence and Machine Learning (AI/ML) to differentiate our company Cloud to our customers. You will help prospective and existing customers and partners understand the power of our company Cloud, develop creative cloud solutions and architectures to solve their business issues, engage in proofs-of-concepts, and troubleshoot any technical questions and roadblocks. You will use your expertise and presentation skills to engage with customers to understand their business and technical requirements, and persuasively present practical and useful solutions on our company Cloud. You will have excellent technical, communication and organizational skills. You will partner with internal engineering stakeholders to improve products and build solutions, optimizing for results when in production and identifying innovative ways to multiply the impact of the team as a whole.

our Cloud accelerates every organizations ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage our companys cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to our company Cloud as their trusted partner to enable growth and solve their most critical business problems.
Responsibilities
Work with the team to identify and qualify business opportunities, understand key customer technical objections, and develop the strategy to resolve technical blockers.
Share in-depth AI/ML expertise to support the technical relationship with customers, including technology advocacy, supporting bid responses, product and solution briefings, proof-of-concept work, and partnering directly with product management to prioritize solutions impacting customer adoption to our company Cloud.
Work directly with our company Cloud products to demonstrate and prototype integrations in customer and partner environments.

we are a fast-growing digital health SaaS company thats on a mission to transform the way physicians interact with patient data. Thousands of clinicians across the United States already use our companys AI-powered solution that transforms complex and fragmented patient data into concise patient portraits" and actionable clinical insights at the point of care. With our company, physicians experience less burnout, reduce missed diagnoses, and can devote more time giving better care to their patients.
our company has been named one of the Top 100 AI companies globally by CB Insights and made the list of the Top 50 Digital Health startups. We are already working with industry-leading value-based organizations including Privia Health and Agilon.
We're looking for talented, versatile and highly independent Machine Learning Engineers to join our winning team. You will be in charge of end-to-end development and you'll have a massive impact on the product and the technical decisions made.
The ML Engineers are part of our infrastructure group, working closely with the exceptional research team, taking trained models and scaling them out to production.
Responsibilities
Take ownership of the entire machine learning engineering lifecycle - from building scalable training and evaluation pipelines to deploying models in production, with robust monitoring and maintenance systems.
Help in creating scalable solutions by enabling us to continuously increase the accuracy of our algorithms across thousands of clinics.
Designing a secured large-scale system that is suitable for sensitive patient data.
Continue to enhancing our deep learning infrastructure to supports our AI models at scale, including CI/CD, automation, testing and monitoring.
Collaborate with the research, medical and product teams in implementing ML solutions to the digital health space.

Are you a MS or PhD student interested in a 2026 internship in the field of machine learning, deep learning, generative AI, large language models, speech technology, robotics, computer vision, optimization, operations research, quantum computing, automated reasoning, or formal methods? If so, we want to hear from you!

We are looking for students interested in using a variety of domain expertise to invent, design and implement state-of-the-art solutions for never-before-solved problems.

Key job responsibilities
As an Applied Science Intern, you will own the design and development of end-to-end systems. Youll have the opportunity to write technical white papers, create roadmaps and drive production level projects that will support our Science.

You will work closely with our scientists and other science interns to develop solutions and deploy them into production. You will have the opportunity to design new algorithms, models, or other technical solutions whilst experiencing our customer focused culture.

The ideal intern must have the ability to work with diverse groups of people and cross-functional teams to solve complex business problems.

Were looking for a seasoned and driven Team Lead to head our NLP & Speech team. In this role, youll lead a high-performing team of researchers and engineers developing state-of-the-art capabilities in real-time transcription, semantic understanding, content generation, and AI-powered editing tools. Leveraging our unique access to vast multimodal datasets and large-scale compute, your team will drive ambitious applied research projects from concept to deployment - powering intelligent, intuitive experiences for millions of content creators.
As a hands-on team lead, youll shape the technical roadmap for NLP and Speech at our company, identifying key opportunities to invest in foundational technologies and grow the team through strategic hiring and mentorship. Youll work cross-functionally with product, engineering, and design partners to ensure that advanced research translates into robust, scalable features that define the future of AI-assisted content creation.

As a key member in our team, you will manage and lead quality assurance processes, provide actionable insights, and help streamline data monitoring and alert systems. If you have a passion for improving processes, and driving data accuracy in consumer intelligence, we want to hear from you!

Responsibilities:

In-Depth Data QA and Oversight: Continuously evaluate and improve data monitoring and QA processes to enhance team efficiency and data quality. Implement best practices and create standard operating procedures for data verification, analysis, and alert management.

Quality Assurance Supervision: Oversee the regular QA checks conducted on partnership intelligence dashboards to ensure data integrity and consistency. Take a proactive role in resolving discrepancies and ensure the timely delivery of accurate reports.

Data Analysis & Reporting: Lead the analysis of trends and patterns in affiliate performance data to uncover areas for improvement. Prepare and present findings to internal teams in an easily understandable format.

Alert Management Oversight: Supervise the alert management system to ensure relevant alerts are delivered accurately to clients in a timely manner. Work with the team to assess the impact of alerts and determine corrective actions based on client preferences.

Cross-Functional Collaboration: Work closely with internal teams to foster communication and collaboration, ensuring alignment between the QA team and other departments such as R&D.

Are you a software engineer who thrives on designing and building scalable, high-quality services and infrastructure? Do you want to work on cutting-edge services while shaping the backbone of an ML platform? If so, wed love to have you join our company ML.
As a Senior Software Engineer, you will play a critical role in architecting and developing cloud based core services and infrastructure with a strong emphasis on clean code, performance, observability, monitoring, and security. This role also includes developing core Go/Java libraries, cross-cutting services like authentication and authorization, Kubernetes deployments, billing etc. You will collaborate closely with engineering teams, DevOps, architects, and product managers to ensure a scalable, stable, and high-performing system.
As a Senior Software Engineer at our company ML you will...
Write clean, maintainable, and efficient code following best practices.
Design and develop robust backend services with scalability, performance, and security in mind.
Conduct high-quality code reviews and architecture discussions, ensuring best practices are followed.
Take full ownership of projects - from ideation and design to production deployment and maintenance.
Collaborate with cross-functional teams to define, design, and ship new features.
Stay current with industry trends, technologies, and best practices in software development and cybersecurity.
Be involved in multiple aspects of an ML platform - from data sources to inference pipelines.