We’re looking for a Senior Data Scientist with strong hands-on experience in fine-tuning Large Language Models (LLMs) on proprietary data. You’ll work at the intersection of research and production, delivering high-performance, business-ready AI solutions.
What You’ll Do
- Prepare and curate proprietary datasets for LLM fine-tuning
- Fine-tune models using LoRA, QLoRA, GRPO, and related techniques
- Benchmark, evaluate, and iterate on model performance
- Deploy fine-tuned models into production inference pipelines
- Stay current with cutting-edge LLM research and apply relevant advances
- Collaborate with product, engineering, and business stakeholders
What We’re Looking For
- Proven experience fine-tuning LLMs on private/proprietary data
- Strong background in ML, NLP, and deep learning
- Hands-on with PyTorch or TensorFlow and Python
- Experience with Hugging Face Transformers
- Solid data skills (Pandas, NumPy) and Git-based workflows
- Strong communication skills and collaborative mindset
Nice to Have
- Experience with RAG / GraphRAG, reasoning or agentic models
- Research background or publications in AI/ML/NLP
- MLOps exposure and model deployment experience
- MS or PhD in a relevant field
What do we offer you?
- Attractive salary
- Large freedom and real influence
- No unhealthy competition, team approach to meeting challenges
- Remote-first, flexible working culture
- Company apartments in cool cities across Europe: work and enjoy a memorable getaway
About Us
We are a software house with 18 years of experience and a global portfolio of projects. We help businesses modernize, scale, and innovate through custom software solutions — always with a focus on flexibility and quality. Our team embraces unconventional ideas and new technologies, delivering solutions that drive real impact. If you value professionalism, creativity, and a strong engineering culture, you'll feel at home here.
Job Type: Full-time
Pay: €54,000.00-€120,000.00 per year
Experience:
- Data Scientist: 5 years (required)
Work Location: Remote