Senior Data Scientist - NLP/LLM

תאור משרה

At our AI & GAI division, you’ll face one of the most exciting challenges in the field — developing on-prem Hebrew LLMs that will power
future decision-support systems for defense-grade solutions. You’ll drive the technical execution and vision of NLP & LLM innovations that pave the way for smarter
language-aware systems, shaping next-generation interfaces and analytics capabilities

We’re looking for

An experienced Data Scientist who lives and breathes NLP and LLMs. Someone eager to build meaningful technology from the ground up
with curiosity, collaboration, and impact at heart. You’ll work side-by-side with Data and AI engineers, review system architectures
mentor teams, and push the boundaries of how generative AI is applied in real operations

Responsibilities

Lead the development and implementation of NLP and LLM solutions for text classification, sentiment analysis, and named entity recognition
Design and implement advanced generative capabilities for decision-support tools based on GAI
Collaborate with cross-functional teams to deploy NLP models in production and optimize performance and scalability
Develop effective text representations to transform natural language into practical features
Provide technical guidance to engineers and serve as a hands-on technical lead
Train embedding and semantic search models (long chain, multi-agent, RAG architecture) within an on-prem environment
Explore new technologies and contribute innovative ideas in the LLM domain

Requirements

M.Sc. in Computer Science or Data Science
At least 5 years of practical experience in ML/DL development
Minimum 3 years of hands-on experience building NLP/LLM systems (on-prem or cloud)
Expert-level understanding of data science methodologies and AI systems
Solid grasp of Agile and DevOps principles
Familiarity with public cloud big data and AI services — Advantage
Active engagement with the LLM community (Git, Hugging Face) — Advantage
Team player with strong interpersonal skills and a broad system perspective
Hands-on technical leadership capabilities