לוח משרות דרושים NLP/Machine Learning משרה מלאה

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

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.

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.

Required Data Infrastructure Engineer
What Youll Do:
Design, implement, and enhance robust and scalable infrastructure that enables efficient deployment, monitoring, and management of machine learning models in production. In this role, you will bridge the gap between research and production environments, streamline data and feature pipelines, optimize model serving, and ensure governance and reproducibility across our ML lifecycle.
Responsibilities:
Decouple data prep from model training to accelerate experimentation and deployment
Build efficient data workflows with versioning, lineage, and optimized resource use (e.g., Snowflake, Dask, Airflow)
Develop reproducible training pipelines with MLflow, supporting GPU and distributed training
Automate and standardize model deployment with pre-deployment testing (E2E, dark mode)
Maintain a model repository with traceability, governance, and consistent metadata
Monitor model performance, detect drift, and trigger alerts across the ML lifecycle
Enable model comparison with A/B testing and continuous validation
Support infrastructure for deploying LLMs, embeddings, and advanced ML use cases
Manage a unified feature store with history, drift detection, and centralized feature/label tracking
Establish a single source of truth for features across research and production across research and production.

We are seeking an AI/ML Lead Engineer to join our R&D division and drive the adoption of advanced machine learning and AI solutions across our financial and operational domains. In this role, you will design and implement intelligent models that increase efficiency in collections and payments processing and build AI-driven tools that enhance call center performance and agent productivity.
We are looking for a hands-on, independent team player with strong foundations in data science, computer science, and backend engineering, combined with excellent analytical and algorithmic skills. This role is diverse and impactful, spanning machine learning development, data analysis, and backend engineering, with the opportunity to shape our AI/ML strategy for servicing and operations.
As part of the R&D group, you will work closely with engineers and product managers, leading and implementing AI/ML initiatives that directly align with our business goals and innovation vision.
Key Responsibilities
Lead the design, development, and deployment of ML models to optimize collections and payments processing.
Develop and integrate AI-driven tools to improve call center efficiency and agent productivity.
Collaborate cross-functionally with engineers, product managers, and stakeholders to translate business needs into technical solutions.
Drive data analysis and modeling efforts, leveraging advanced algorithms to uncover insights and improve decision-making.
Ensure scalability, quality, and compliance of all AI/ML solutions within the financial and servicing domains.
Stay up to date with emerging AI/ML technologies and assess their potential impact on the companys strategy.
Mentor and guide team members, fostering knowledge-sharing and technical excellence.

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