לוח משרות דרושים NLP/Machine Learning

Were hiring an AI Backend Engineering Manager to guide and grow a high-impact ML team driving AI-powered innovation across B2B SaaS platform. Youll lead the design and delivery of AI solutions while mentoring engineers and setting the technical direction for AI-first development at scale.
This is a leadership role with a balance of hands-on engineering and team management, perfect for someone who thrives on solving technical challenges, inspiring a team, and shaping the future of AI in fintech automation.
What You Will Do:
Lead & Mentor: Manage, mentor, and grow a team of AI/ML/Backend engineers, fostering technical excellence and career development.
Set Technical Direction: Define the ML strategy, ensuring best practices in architecture, frameworks, and operationalization.
Build and deploy AI-based solutions: Oversee the development and deployment of GenAI/LLM-powered solutions that address real-world challenges across products.
Scale & Operationalize: Establish scalable ML infrastructure, CI/CD, observability, and data pipelines for high-availability production systems.
Collaborate Cross-Functionally: Partner with product managers, engineers, and business stakeholders, clearly communicate progress, challenges, and outcomes.

we are looking for an experienced Data Science Manager to lead and grow our Data Science team. This is a managerial role focused on leading a team of Data Scientists while driving the strategy, execution, and delivery of impactful AI and ML initiatives across our SaaS platform.
You will be responsible for both people leadership and technical direction - ensuring high standards of execution, mentoring team members, and aligning data science efforts with product and business goals. This role requires a strong hands-on background combined with proven team management experience.
What You Will Do:
Lead, mentor, and manage a team of 7-10 Data Scientists, fostering a culture of ownership, excellence, and continuous learning.
Own the teams roadmap, prioritization, and delivery of AI initiatives.
Provide technical and architectural guidance across projects.
Drive end-to-end execution of data science solutions - from problem definition and research to modeling, evaluation, deployment, monitoring and enhancement cycles.
Collaborate closely with Product, Engineering, and Business stakeholders to translate business needs into scalable AI solutions.
Ensure production-grade standards, model performance monitoring, and continuous improvement.
Stay up to date with advances in machine learning, GenAI, and LLM technologies, and translate them into business impact.
Take responsibility for hiring, onboarding, and developing top data science talent.

Lead the charge in transforming our product and preparing it for the agentic age.
Design, build, and deploy generative AI-powered features across our product.

Identify opportunities for AI integration by proactively exploring FinOps use cases and user needs

Prototype and validate new AI use cases quickly and iterate based on internal and external feedback

Collaborate cross-functionally with product, design, and backend teams to drive innovation from concept to production

Stay current with the fast-moving generative AI landscape and evaluate new models, APIs, and tools (e.g., OpenAI, Anthropic, Hugging Face, AWS Bedrock, open-source LLMs).

Live in the future and track new innovations and paradigms in this fast evolving field and identify opportunities to integrate them into the product

Implement safeguards, prompt engineering techniques, and usage monitoring to ensure high-quality AI outputs

Optimize model performance, inference time, and cost efficiency within AWS infrastructure

Do you want to take part in shaping the future of AI-driven materials discovery? We are seeking a talented and highly motivated student for a Joint PhD at Bar-Ilan University (BIU), to conduct cutting-edge research in collaboration with our teams, on next-generation Foundation Models for Materials Science.
The work will focus on developing novel multi-modal foundation models for materials discovery, leveraging large-scale data, representation learning, and uncertainty estimation. The candidate will work closely with academic and industry researchers, contributing to both methodological advances and real-world impact across scientific and industrial domains.
What youll be doing:
Conduct research in deep learning and AI for materials science, with a focus on foundation models, multi-modal learning, and representation learning.
Develop and train large-scale models for materials discovery and prediction tasks.
Collaborate with researchers and engineers across and academia.
Lead independent research under academic supervision, while contributing to team efforts.
Publish results in top-tier conferences and journals, and present findings clearly and effectively.

We are looking for a Software Engineer specializing in ML systems Engineering to join Development department.
While vision and language models have become increasingly commoditized, proprietary deep learning models are unique, fast-evolving, and deployed in live trading across the worlds most efficient and sophisticated financial markets. Operating in this environment presents distinct scaling challenges and continuous opportunities for optimization. Success in this role requires first-principles thinking and a deep understanding of the engineering trade-offs behind high-performance DL systems.
This is a pivotal role within engineering organization. You will work closely with researchers and engineers across the company, running deep learning models on massive compute clusters and adapting them for production serving under strict and non-trivial constraints.

Our unique research team is expanding, we are looking for smart and humble team members to join the team and solve complex problems.
Our technical challenges include developing new trading strategies, , improving the performance of our algorithms, finding new ways to beat the markets.
As an ML researcher you will collaborate with our R&D team to execute live trading strategies. If you are looking to make an impact by putting into practice successful ideas and seeing immediately the outcome, make influence on financial performance this is a great opportunity.

We are always looking for exceptional talent to join us on the journey!
We are always looking for exceptional talent to join us on the journey!


Your Mission

As an MLOps Engineer at Nuvei, your mission is to design, build, and operate the platforms that power our machine learning and generative AI products spanning real-time use cases such as large-scale fraud scoring, MCP & agentic workflows support. Youll create reliable CI/CD for models and Agents, robust data/feature pipelines, secure model serving, and comprehensive observability. You will also support our agentic AI ecosystem and Model Context Protocol (MCP) services so that models can safely use tools, data, and actions across .
You will partner closely with Data Scientists, Data/Platform Engineers, Product, and SRE to ensure every model from classic ML to LLM/RAG agents moves from prototype to production with strong reliability, governance, cost efficiency, and measurable business impact.
Responsibilities:
Operate & Develop ML/LLM platforms on Kubernetes + cloud (Azure; AWS/GCP ok) with Docker, Terraform, and other relevant tools
Manage object storage, GPUs, and autoscaling for training & low-latency model serving
Manage cloud environment, networking, service mesh, secrets, and policies to meet PCI-DSS and data-residency requirements
Build end-to-end CI/CD for models/agents/MCP tooling (versioning, tests, approvals)
Deliver real-time fraud/risk scoring & agent signals under strict latency SLOs.
Maintain MCP servers/clients: tool/resource definitions, versioning, quotas, isolation, access controls
Integrate agents with microservices, event streams, and rule engines; provide SLAs, tracing, and on-call runbooks
Measure operational metrics of ML/LLM (latency, throughput, cost, tokens, tool success, safety events)
Enforce governance: RBAC/ABAC, row-level security, encryption, PII/secrets management, audit trails.
Partner with DS on packaging (wheels/conda/containers), feature contracts, and reproducible experiments.
lead incident response and post-mortems.
Drive FinOps: right-sizing, GPU utilization, batching/caching, budget alerts.

We are looking for a Senior Software Engineer to join our Video/Multimedia Architecture & Algorithms (A&A) team - the people who build tomorrows NVENC and NVDEC, the dedicated video encode and decode engines that power streaming, cloud gaming, video conferencing and broadcast on every modern GPU. You will lead the infrastructure and operations for this groups work. This includes setting up compute resources on-premises and in the cloud. You will develop distributed pipelines for large-scale regressions and experiments across hardware simulations and machine learning workloads. You will maintain the CI/CD and development environments. You will also transform one-off research workflows into reliable, repeatable, automated systems.
This is a hybrid role - 4 days per week from the office.
What You'll Be Doing
Work closely with our Architects and Algorithms Engineers to understand the needs and transform one-off research workflows into dependable, consistent, automated systems
Stand up and operate the compute the group runs on - on-prem GPU clusters, cloud bursts, queues, schedulers (Slurm / Kubernetes), container images, environments
Develop and build decentralized workflows for extensive regression testing and experiments across HW-simulations and ML workloads - and the dashboards that make sense of the results
Lead the teams CI/CD plus the dev environments, container images and tooling everyone in the group lives in every day.

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.

we are looking for a Senior Machine Learning Engineer to work on LLM-based systems with a strong emphasis on integration, end-to-end workflows, and production readiness. This role combines performance optimization (prefill/decode, throughput, latency) with hands-on work integrating components across the AI platform.
A significant part of the role involves building end-to-end integration flows and tests, particularly around token generation pipelines and system orchestration, as well as contributing to intelligent system behavior such as hardware selection and execution strategies. The role also includes developing system-level logic in Python for multi-tenant management, caching strategies, and service lifecycle management across the platform.
***This is not a Data Science position***
Responsibilities:
Build and maintain end-to-end integration flows across the AI inference pipeline (serving, orchestration, APIs, and infrastructure)
Design, implement, and optimize LLM inference workflows, including prefill and decode stages
Improve system performance with focus on throughput, latency, and interactivity
Write production-grade components in Python and integrate them into the broader system
Contribute to system-level logic such as smart hardware selection and execution strategies
Integrate models (open source and custom), services, and APIs into cohesive, reliable end-to-end application pipelines

Required Staff Software Engineer, Cloud Storage, AI/ML
Tel Aviv, Israel
Responsibilities
Design and implementation of high-complexity features. Deliver production-ready code for storage solutions that address the specific demands of AI/ML workloads.
Architect scalable and performant storage solutions. Make data-driven decisions to optimize system efficiency and reliability.
Identify and resolve performance bottlenecks and intricate system issues. Develop innovative, practical solutions to technical issues that arise at the intersection of storage and ML.
Partner with product and engineering stakeholders to translate customer requirements into technical specifications, ensuring the incubations output aligns with broader Cloud goals.

The financial risk management (FRM) machine learning principal will be the most senior machine learning engineer and strategist for financial risk at Meta. 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 Metas 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 Metas 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 Meta's risk management system. - Collaborate with Principal ML engineers from across the company to adopt best industry and Meta 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 Meta
Identify and Initiate New Business Opportunities: - Collaborate with Meta 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 highly skilled Data Engineer to join our growing Data Analytics Department.

As a Data Engineer in a multi cloud company, you will build data-driven solutions for our customers using cutting-edge data tools and large-scale data on AWS\GCP\Azure.

Job Responsibilities:

Lead data solutions design and development for our various clients and projects.
Design the solution by understanding the needs, modeling the data, choosing the right tools and defining the interfaces/dashboards.
Develop Data Pipelines, Data Lakes, DWHs, AI\ML models, Dashboards and reports using advanced tools and leading technologies.

Are you an AI Analyst ready to translate raw model output into a reliable, high-quality production system? Do you excel at the craft of Prompt Engineering and thrive on the challenge of ensuring Generative AI output meets rigorous quality standards in mission-critical applications? Join our R&D Operations Team. You will be the AI analyst responsible for the end-to-end quality, performance, and operational tuning of our Generative AI-driven support system (Co-Pilot). Your mission is to actively shape the model's intelligence, govern the data it uses, and implement the mechanisms that guarantee its accuracy, directly accelerating our customer support engineering velocity.
Key Responsibilities
Support & Customer Advocacy: Champion the Support Journey in Engineering. Develop in-product support instructions that reflect and address real incoming cases, enhancing the quality and effectiveness of AI feature solutions.
Model Quality Validation: Use existing evaluation platforms and methodologies to validate production models. Monitor quality metrics to continuously assess and rank AI answers for accuracy and reliability.
Prompt Engineering & CT Loop: Drive the Continuous Training loop through systematic prompt engineering (refining and versioning inputs). Analyze failures to define R&D actions or features needed to close model performance gaps.
AI Knowledge Governance: Act as AI Content Governor, implementing controls to verify and ingest compliant knowledge base content, ensuring a quality data source.
Cross-Functional SME: Serve as the AI Support Co-pilot Subject Matter Expert, partnering with R&D and Support Enablement to translate quality issues into core model logic improvements and feature development.