AI Engineer/Data Scientist
Are you passionate about Natural Language Processing and Generative AI? Do you enjoy collaborating with both technical and business teams to turn innovative ideas into impactful solutions? Can you communicate complex concepts clearly and drive research that delivers real business value? If so, we have an exciting opportunity for an AI Engineer/Data Scientist to join EPAM’s AI Consulting team, focusing on cutting-edge R&D in Large Language Models (LLMs), Retrieval-Augmented Generation (RAG) and domain-specific GenAI applications.
If you’re ready to push the boundaries of NLP and GenAI and want to make a tangible impact, we’d love to hear from you!
Responsibilities
- Design, implement and maintain scalable NLP and GenAI pipelines including data processing, preprocessing and evaluation
- Conduct advanced data analysis on real-world datasets to extract actionable insights and support decision-making
- Stay current with the latest research in LLMs and NLP, proposing new ideas and methodologies to unlock business value
- Develop and optimize RAG systems and retrieval pipelines including chunking, embedding, re-ranking and evaluation
- Lead and contribute to experiments by designing experimental details, writing reusable code, running evaluations and organizing results
- Collaborate with cross-functional teams to prioritize research that directly benefits key internal use cases and products
- Work closely with stakeholders, project managers and architects to gather requirements, plan project scopes and deliver projects on time
Requirements
- MSc with 5+ years of experience or Ph.D. in computer science, electrical engineering or a related technical field
- Deep understanding of NLP, LLMs, transformer architectures, prompt engineering, RAG and evaluation methodologies
- Strong Python programming skills for developing and debugging AI models
- Hands-on experience building and evaluating RAG and GenAI systems in production-like environments
- Experience training, fine-tuning or experimenting with foundation models
- Track record of contributions to publications or open-source projects
- Excellent communication skills and a collaborative mindset
- Experience mentoring or collaborating with other researchers
- Strong interest in cross-disciplinary collaboration to support impactful research
- Ability to work effectively across teams and deliver projects within agreed timelines
