Data Scientist - JB-745

Our mission is to build and maintain cutting-edge technological infrastructures that empower innovation in the fields of data and artificial intelligence. Join us to lead the development of scalable, next-generation platforms that enable meaningful transformation and impact.

We are looking for an Data Scientist to join our NLP team.

The role combines research, model development, and hands-on engineering, spanning from training and evaluating large language models to building AI-powered applications and production systems.

The ideal candidate is someone who can take ownership of complex problems, independently explore new approaches, and turn research ideas into impactful, real-world AI solutions.

Role Overview

• Develop cutting-edge research and engineering solutions in Large Language Models (LLMs) and Generative AI.
• Work across the full lifecycle of foundation model development — from research and experimentation to scalable training and production infrastructure.
• Develop advanced LLM solutions and AI-powered applications, including chatbots, agents, and other GenAI systems using modern AI APIs and frameworks.

Key Responsibilities

• Conduct applied research on LLM training methodologies, optimization, and evaluation.
• Train, fine-tune, and evaluate large-scale language models.
• Design experiments and domain-specific benchmarks to measure model performance and behavior with statistically rigorous evaluations.
• Monitor and analyze the behavior and performance of AI models and agents.
• Build and maintain infrastructure for distributed training and large-scale experimentation.
• Develop ML models and AI applications in Python and integrate them with modern agent-based systems.
• Collaborate with researchers and engineers to transform research ideas into production-ready solutions.
• Continuously evaluate new research and implement state-of-the-art techniques across a wide range of domains, including healthcare, defense, finance, government, and more.

Requirements

• 4+ years of experience in ML, Data Science, or AI Engineering.
• Hands-on experience training and fine-tuning large neural networks.
• Hands-on experience with modern LLM technologies, including RAG, SFT, RLHF/DPO, and high-performance inference frameworks (e.g., vLLM).
• Experience with GPU-based training environments and large-scale ML infrastructure.
• Strong Python and software engineering skills, including experience developing ML models, production AI systems and modern LLM/agent frameworks and APIs (e.g. PyTorch, Hugging Face, CUDA, vLLM, LangChain)
• Strong analytical and research skills, with the ability to independently investigate and solve complex problems.
• Self-driven, highly motivated, and able to take ownership of challenging projects.