Senior Data Scientist (Applied AI / LLM) at Nebius

Tel Aviv, IsraelFull-timeData & AnalyticsPosted 15 days ago

About the Role

<div class="content-intro">About Nebius: Nebius is leading a new era in cloud infrastructure for the global AI economy. We are building a full-stack AI cloud platform that supports developers and enterprises from data and model training through to production deployment, without the cost and complexity of building large in-house AI/ML infrastructure. Built by engineers, for engineers. From large-scale GPU orchestration to inference optimization, we own the hard problems across compute, storage, networking and applied AI. Listed on Nasdaq (NBIS) and headquartered in Amsterdam, we have a global footprint with R&D hubs across Europe, the UK, North America and Israel. Our team of 1,500+ includes hundreds of engineers with deep expertise across hardware, software and AI R&D.</div><h3>The role</h3> Nebius is looking for a Senior Data Scientist (Applied AI / LLM) to design, build, and deploy production-grade AI systems based on large language models. You will focus on turning LLM capabilities into reliable, measurable business solutions, while also contributing to predictive modeling across different business domains. Your work will include building evaluation frameworks, improving model accuracy, and developing agent-based systems that automate analytical and data workflows (e.g., data quality monitoring). The role emphasizes production readiness, robustness, and real business impact—not experimentation. You’re welcome to work in our office in Tel Aviv. Your responsibilities will include:  <ul> <li>LLM system development. Design and deploy LLM-based solutions (e.g., RAG pipelines, agent workflows) for real business use cases.</li> <li>Evaluation & reliability. Build evaluation frameworks to measure accuracy, consistency, and failure modes of LLM systems. Continuously improve performance based on real-world usage.</li> <li>Agent-based automation. Develop agentic solutions to automate workflows such as data quality checks, anomaly detection, and reporting.</li> <li>Applied predictive modeling. Apply classical ML and statistical methods to business domains such as HR and Finance (e.g., forecasting, classification, risk modeling).</li> <li>Production & MLOps. Deploy and maintain models in production, ensuring monitoring, versioning, and scalability.</li> <li>Stakeholder collaboration. Translate business needs into AI/ML solutions and communicate trade-offs, risks, and performance clearly.</li> <li>Cross-domain contribution. Contribute to adjacent areas (e.g., forecasting models) to ensure team redundancy and shared ownership of critical workflows.</li> </ul> We expect you to have:  <ul> <li data-start="1717" data-end="1787">Experience as a data scientist or applied ML practitioner (5+ years).</li> <li data-start="1790" data-end="1857">Experience building and deploying LLM-based systems in production.</li> <li data-start="1860" data-end="1943">Experience working in production environments with model monitoring and iteration.</li> <li data-start="1946" data-end="2014">Experience with modern data science and ML ecosystems using Python.</li> <li data-start="2017" data-end="2079">Experience working with large datasets and strong SQL skills.</li> <li data-start="2082" data-end="2151">Understanding of LLM evaluation, prompt design, and system behavior.</li> <li data-start="2154" data-end="2221">Strong foundation in statistics and machine learning fundamentals.</li> <li data-start="2224" data-end="2296">Demonstrated ability to deliver production-grade AI systems end-to-end.</li> <li data-start="2299" data-end="2394">Demonstrated ability to translate business needs into AI/ML solutions and communicate clearly.</li> <li data-start="2397" data-end="2446">Working knowledge of spoken and written English.</li> </ul> It will be an added bonus if you have:  <ul> <li> Experience with RAG architectures and retrieval systems.</li> <li data-start="2561" data-end="2621">Experience designing or working with agent-based workflows.</li> <li data-start="2624" data-end="2679">Experience with MLOps tools and production ML systems.</li> <li data-start="2682" data-end="2743">Experience working in cloud environments (preferably Azure).</li> </ul><div class="content-conclusion">Benefits & Perks: <ul> <li>Competitive compensation</li> <li>Career growth and learning opportunities</li> <li>Flexibility and work-life balance</li> <li>Collaborative and innovative culture</li> <li>Opportunity to work on impactful AI projects</li> <li>International environment and talented teams</li> </ul> What's it like to work at Nebius: Fast moving - Bold thinking - Constant growth - Meaningful impact - Trust and real ownership - Opportunity to shape the future of AI  Equal Opportunity Statement: Nebius is an equal opportunity employer. We are committed to fostering an inclusive and diverse workplace and to providing equal employment opportunities in all aspects of employment. We do not discriminate on the basis of race, color, religion, sex (including pregnancy), national origin, ancestry, age, disability, genetic information, marital status, veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by applicable law. Applicants must be authorized to work in the country in which they apply and will be required to provide proof of employment eligibility as a condition of hire.  If you need accommodations during the application process, please let us know.</div>

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