לוח משרות דרושים NLP/Machine Learning

As a machine learning scientist, your work will focus on building, training and deploying content models (Computer vision, NLP and Generative AI) using the most advanced technologies and models.
You will be responsible for identifying and proposing the most appropriate data sources and modeling techniques to solve complex problems and drive business value.
Key Job Responsibilities and Duties:
Explore and apply state-of-the-art techniques in multimodal machine learning.
Train innovative ML models (NLP, CV, LLM-finetuning), build algorithms, and engineering approaches to drive business impact..
Coding skills: ensure implementation of reusable frameworks (clean and scalable code).
Conduct data analysis with detailed metrics to evaluate models performance, labels quality, features exploration.
Work closely with machine learning engineers to ensure the model's latency/throughput meets product requirements and ensure deployment of your model to production.
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.

As a Machine Learning Scientist, your work will focus on the evaluation and optimization of generative AI systems. You will develop and fine-tune Judge LLMs to assess model outputs across a variety of tasks, design robust evaluation frameworks for agentic workflows, and build scalable pipelines for synthetic data generation. The team also plays a critical role in multilingual evaluation, enabling GenAI applications to support market expansion across all supported languages.
Key Job Responsibilities and Duties:
Develop and apply state-of-the-art techniques for evaluating generative AI systems, with a focus on agent workflows, multilingual output, and task-specific Judge LLMs.
Design and implement scalable evaluation pipelines, including synthetic data generation and benchmarking for model quality, relevance, and consistency..
Optimize and maintain Judge LLMs to assess outputs across dialog systems, Q&A, and trip planning use cases.
Conduct in-depth data analysis to define and track evaluation metrics, validate label quality, and explore performance across different languages and user scenarios.
Ensure the reliability, efficiency, and scalability of evaluation tools and frameworks in both offline and online environments.
Collaborate closely with ML engineers to integrate evaluation components into production pipelines, supporting continuous improvement of GenAI applications.
Work cross-functionally with product, research, and analytics teams to align evaluation strategies with business goals and user impact.

As Senior Machine Learning Engineer, youll work with top notch engineers and data scientists from the team on bringing it to the next level and enabling optimal user experience. The work will focus on building, deploying and serving GenAI capabilities (Agents, Tools and the orchestration between them) using the most advanced technologies and models.
Key Job Responsibilities and Duties:
Deploying machine learning models: Design, develop and deploy in collaboration with scientists, scalable machine learning models and algorithms that provide content related insights and generative AI applications, ensuring scalability, efficiency, and accuracy.
Evaluating possible architecture solutions by taking into account cost, business requirements, emerging technologies, and technology requirements, like latency, throughput, and scale.
Generative AI Development: Contribute to the development of generative models such as GPT (Generative Pre-trained Transformer) variants or similar architectures for creative content generation, Q&A, translation or other innovative applications.
Deployment and integration: Work closely with software engineers to integrate machine learning models into production systems. Ensure seamless deployment and efficient model inference in real-time environments. Collaborate with DevOps to implement effective monitoring and maintenance strategies.
Owning a service end to end by actively monitoring application health and performance, setting and monitoring relevant metrics and acting accordingly when violated.
Maintain clean, scalable code, ensuring reproducibility and easy integration of models into production environments, including CI/CD.
Collaborate with multidisciplinary teams: Collaborate with product managers, data scientists, and analysts to understand business requirements and translate them into machine learning solutions.

In this role, you will lead a team of Machine Learning Scientists and Engineers dedicated to building, training, and deploying cutting-edge Generative AI models. This includes developing foundation models trained on our companys extensive textual data and creating fine-tuned models designed to tackle complex travel-related tasks. Your leadership will play a pivotal role in advancing the application of AI to transform the travel experience for millions of customers.
As a technical manager, you should be passionate about GenAI technology, keep up to date with recent breakthroughs in the field, define and shape the teams ML roadmap, and not be afraid to get your hands dirty with code when needed.
You are expected to be the focal point for all technical aspects, make sure your team members deliver on their tasks, and work together with other stakeholders to define and shape the roadmap of our products. You will work independently and will also be responsible for making technical decisions within your team.
When it comes to management, your expertise in handling people will motivate and inspire them to reach outstanding success! You should have experience in developing people. You will mentor and coach your team while working closely with a Product Manager.
Key Job Responsibilities and Duties:
Leadership in LLM Development- Build, Guide and mentor a team of ML scientists and ML engineers in the development, fine-tuning, and deployment of large language models (LLMs) tailored for the travel domain.
Expertise in the engineering aspects of deploying LLMs at scale with minimal latency. This includes optimizing model performance, scalability, and efficiency to meet the demands of real-time, high-traffic applications.
Define and communicate the technical vision and strategy for LLM-related initiatives, ensuring alignment with company goals and customer needs.
Foster a culture of collaboration, innovation, and excellence within the team.
Prioritize work in collaboration with Product Managers, depending on business needs and keeping stakeholders aligned at all times.
Translate machine learning vision and strategy into planning and execution, and ensure timely delivery of their plans.
Develop innovative ML models, algorithms, and engineering approaches or identify existing ones, with the potential to impact our business.
Design and execute applied research plans to understand, apply, test, evolve, and generalize these technologies into reusable frameworks.
Translate business problems into viable, reliable and robust ML and AI solutions, accounting for constraints of the production environment.
Monitor product health, performance and business impact and act accordingly when requirements are not met.
Identify underlying issues and opportunities across domains and situations that are not obviously related through application of structured thinking and logic.
Solve issues by applying methods and insights gained from a variety of disciplines, navigating a variety of environments.

Were looking for a Product Designer who thinks, works, and designs with AI. Someone whos not just excited about AI-powered features but already uses AI tools in their daily design workflow.

This is a unique opportunity to design GenAI-based features and products while shaping the future of inclusive AI experiences.

Your role: building AI-powered, human-centered experiences

You own the design of AI-powered features and end-user experiences across our products, with a focus on usability, clarity, and impact
You use AI tools (like ChatGPT, Figma Make, Cursor, Bolt, Loveable.ai, Base44 and more) as part of your daily creative process from ideation and wireframing to content generation and design optimization
You collaborate with product managers, engineers, and data or ML teams to create smart, intuitive, and accessible interfaces that are built on AI capabilities
You translate PRDs and GenAI feature specs into experiences that feel simple, safe, and empowering even when the underlying tech is complex
You push boundaries actively experimenting with what AI can enable in product design, both in terms of user experience and your own internal workflows
You combine human-centered thinking with machine-enhanced creativity, constantly exploring ways to improve speed, insight, and output quality using AI
Bonus if you can demonstrate initiative in developing internal tools or plugins that improve design workflows for example: building custom Figma plugins, prototyping with APIs, automating QA tasks, or building mini apps for internal collaboration

Were on a mission to revolutionize how marketers, writers, and innovators create their marketing content. With tools like ChatGPT?? taking the world by storm, its clear that the spotlight is now shining on the Generative AI space. However, its ultimate hurdle is now a self-compounding problem: with infinite options for messaging now available to all marketers how do we know what will actually work? Your words matter, and Anyword was built to ensure that they resonate. Since 2021, weve been building a platform to help both the worlds largest brands and its next rising stars actually move, inspire, and drive their audiences forward. In reality, weve removed the uncertainty of writing performance copy, and are the first to bring copy intelligence into play. Weve combined our own language models, predictive analytics, custom AI, and branding-specific tools to help brands rise above the noise in ways they couldnt before. Weve built the brain behind all marketing messaging, no matter where it lives and how you create it (with AI or not). And now were looking to you to help change the world with us!
About the role Anyword is 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 Anywords AI content platform.
Responsibilities:
* Define and own the technical strategy and roadmap for Anywords 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 highly skilled and motivated MLOps Engineer to join our team and play a critical role in the deployment, automation, and maintenance of our machine learning infrastructure. You will be responsible for ensuring that our ML models move seamlessly from experimentation to production with stability, security, and scalability in mind. You will work closely with data scientists, machine learning engineers, and DevOps teams to build robust model pipelines, manage infrastructure across on-prem and cloud, and enforce best practices in version control, model deployment, and compliance. Key Responsibilities: · Design, implement, and maintain automated model training pipelines using tools such as MLflow, (Kubeflow, Airflow), or custom orchestrators. · Support reproducibility and consistency across model training environments. · Implement and manage Artifactory. · Establish and maintain model registries to track versions, metadata, and lineage. · Automate model promotion through staging, testing, and production environments. · Build CI/CD pipelines tailored for ML use cases, integrating model training, validation, deployment, and rollback. · Manage and scale infrastructure across cloud platforms (Azure) and on-premise environments · Optimize GPU/CPU resource utilization and cost efficiency. · Implement auto-scaling and load balancing strategies for ML workloads. · Manage version control systems (e.g., Git) and integrate with experiment tracking tools. · Handle storage and retrieval of artifacts (e.g., Docker images, models, datasets) via artifact registries like JFrog Artifactory or AWS ECR.

We are looking for a highly skilled AI Engineer with a strong engineering mindset to bridge the gap between research and production.

In this role, you will be responsible for validating AI models developed by our Data Science team against real-world production systems, and then leading their optimization, deployment, and ongoing maintenance.

You will be part of the R&D team, working closely with engineers, data scientists, and product managers to ensure our AI solutions are scalable, reliable, and deliver long-term value.

If you enjoy working at the intersection of AI and engineering bringing models to life in production, optimizing for performance, and building reliable systems this role is for you!

Responsibilities
Lead the transition of AI models from proof-of-concept to full-scale production, ensuring they meet architectural, scalability, and performance standards.
Build observability and troubleshooting tools for AI services in production, including logging, performance tracking, and failure analysis pipelines.
Optimize inference performance, including latency, resource usage, and throughput, while maintaining model quality.
Manage model versioning and deployment readiness, including handoff processes, rollback plans, and configuration management.
Partner with the Data Science team to assess model readiness for production, validate input and output compatibility, and ensure assumptions align with real-world system behavior.
Collaborate cross-functionally with DevOps, backend engineers and data scientists to ensure scalable, secure, and cost-effective deployment of ML models

What We Are Looking For As a VP of AI Security Research you will lead, scale, and inspire multi-disciplinary teams focused on red teaming, sandboxing, adversarial testing, developing red-teaming engines, and guardrail protections for GenAI models and agentic AI systems. In this high-profile role, you will work closely with security research, product, engineering, and compliance teams to shape and deliver the next generation of AI cybersecurity solutions, while combining strategic vision with execution to effectively safeguard LLMs and agentic AI deployments at scale. Key Responsibilities
* Building and scaling global AI security teams, while providing mentorship to senior managers and fostering an innovation-driven security culture.
* Overseeing advanced adversarial evaluations for GenAI models, agentic AI, and multi-agent (A2A) systems, and delivering executive-level threat intelligence and risk assessments to inform corporate AI strategy.
* Defining and implementing AI red-teaming frameworks aligned with OWASP AI Security guidelines, MITRE ATLAS, and NIST AI RMF, and operationalizing automated red-team engines to continuously stress- TEST models at scale.
* Partnering with product and engineering to design and deploy enterprise-ready AI guardrails, including policy enforcement layers, monitoring pipelines, and anomaly detection systems and championing secure deployment practices for GenAI (including agent orchestration via MCP and A2A workflows).
About ActiveFence:
ActiveFence is the leading provider of security and safety solutions for online experiences, safeguarding more than 3 billion users, top foundation models, and the worlds largest enterprises and tech platforms every day. As a trusted ally to major technology firms and Fortune 500 brands that build user-generated and GenAI products, ActiveFence empowers security, AI, and policy teams with low-latency Real-Time Guardrails and a continuous Red Teaming program that pressure-tests systems with adversarial prompts and emerging threat techniques. Powered by deep threat intelligence, unmatched harmful-content detection, and coverage of 117+ languages, ActiveFence enables organizations to deliver engaging and trustworthy experiences at global scale while operating safely and responsibly across all threat landscapes.
Hybrid:
Yes

ActiveFence is a leading platform for Trust & Safety teams worldwide, leveraging cutting?edge AI and world?class expertise to protect users from the widest spectrum of online harms. By continuously collecting and analyzing data, our solutions ensure customers stay two steps ahead of bad actors in an ever?changing threat landscape. As we expand our generative AI initiatives to enhance online safety, we’re seeking an outstanding AI?Workflow?Automation Engineer to join our GenAI research team . In this role, you’ll build, scale and automate the workflows powering our large?scale, AI?driven content moderation and generative model deployments, enabling real?time protection for billions of users. Key Responsibilities
* Build and maintain CI/CD pipelines that support fast, reliable integration and deployment of GenAI systems across complex environments, including orchestrating multiple models/agents and MCP clients/servers.
* Develop, deploy and integrate AI solutions and agentic frameworks, creating both command?line tools and interactive notebooks that support our team’s research and workflow automation needs.
* Build and manage data pipelines and databases (SQL) for large?scale data handling, automating data collection and curation (e.g., adversarial prompts for model red-teaming) to support AI training and evaluation.
* Integrate research into production by implementing the latest generative AI advancements (including white?box LLM development), integrating different models and agents, and developing evaluation frameworks (e.g., agentic reasoning tests) as part of our automated workflows.
* Deploy GenAI models from repositories such as HuggingFace onto our AWS platform, connect them to data pipelines, and automate end?to?end processes for prompt generation, labeling, and response evaluation.


About ActiveFence:
ActiveFence is the leading provider of security and safety solutions for online experiences, safeguarding more than 3 billion users, top foundation models, and the world’s largest enterprises and tech platforms every day. As a trusted ally to major technology firms and Fortune 500 brands that build user-generated and GenAI products, ActiveFence empowers security, AI, and policy teams with low-latency Real-Time Guardrails and a continuous Red Teaming program that pressure-tests systems with adversarial prompts and emerging threat techniques. Powered by deep threat intelligence, unmatched harmful-content detection, and coverage of 117+ languages, ActiveFence enables organizations to deliver engaging and trustworthy experiences at global scale while operating safely and responsibly across all threat landscapes.

The GenAI team builds conversational experiences that feel human and decision engines that learn on their own. If moving from prototype to production with millions flowing through it gets you buzzing, keep reading.

In this role you'll:
Design, build, and own end-to-end Generative-AI services from first prompt to production rollout

Combine retrieval-augmented generation (RAG), function calling, and agents to automate underwriting, claims, and customer support flows

Fine-tune open-source and commercial LLMs on proprietary datasets, evaluate with both offline benchmarks and online A/B tests

Collaborate with product, data science, and design to invent new AI-first customer experiences (and kill the bad ones fast)

Build scalable APIs and micro-services (TypeScript/NestJS or Python/FastAPI) running in Kubernetes on AWS

Instrument, monitor, and continuously improve model quality, latency, and cost you ship it, you own it

Mentor fellow engineers on GenAI best practices: prompt engineering, vector search, safety & guard-rails

Contribute to internal tooling that automates the boring stuff (CI/CD, sandbox environments, branch deploys)

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.

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.