Data Scientist (LLM & Generative AI) | Tel Aviv (Hybrid)

A global AI company is looking for a talented Data Scientist to join its R&D team and help build the next generation of AI-powered products.

This is not a traditional Data Science role focused on dashboards or analytics. We are looking for a hands-on, product-oriented Data Scientist who enjoys working at the intersection of Machine Learning, Generative AI and real-world production systems.

You will be involved in designing, developing and deploying advanced AI solutions based on LLMs, Agentic AI, Retrieval and Semantic Search technologies, working closely with Product and Engineering teams to deliver impactful AI capabilities to a global SaaS platform.

Responsibilities

Design, build and deploy Machine Learning and Deep Learning models in production environments

Develop and improve LLM-based applications and Generative AI solutions

Build Retrieval, Semantic Search and Ranking systems

Improve model quality, performance and evaluation processes

Work closely with Product, Engineering and AI teams

Own projects end-to-end, from exploration and modeling to deployment, monitoring and iteration

Requirements

3–5 years of experience as a Data Scientist, Machine Learning Engineer or similar role

Proven experience deploying models to production

Strong Python development skills

Solid understanding of Machine Learning and Deep Learning

Experience with Docker and Kubernetes

Experience working with Cloud platforms (AWS, GCP or Azure)

Experience with PyTorch or TensorFlow

Experience working in product-oriented R&D environments

Nice to Have

Experience with LLMs and Generative AI

Experience with RAG (Retrieval-Augmented Generation)

Experience with Semantic Search and Retrieval systems

Experience with Vector Databases

Experience with LangChain, LlamaIndex or similar frameworks

Experience building AI-powered SaaS products

📍 Location: Tel Aviv (Hybrid)

If you're passionate about building real-world AI products and taking models from idea to production, we'd love to hear from you.

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