Data Scientist

We are looking for an experienced Data Scientist with deep expertise in fine-tuning large language models (LLMs) using proprietary data. This role is ideal for someone who thrives at the intersection of data preparation, model optimisation, and applied research—and who is eager to stay ahead of the latest AI advancements.

Key Responsibilities

• Design, curate, and preprocess datasets for fine-tuning on proprietary data.
• Fine-tune LLMs using advanced techniques (e.g., LoRA, QLoRA, GRPO).
• Benchmark model performance, analyze trade-offs, and ensure state-of-the-art results.
• Deploy fine-tuned models into production for reliable inference.
• Monitor and evaluate emerging research (e.g., recent arXiv publications) to identify opportunities for improvement.
• Collaborate with engineering and product teams to integrate optimized models into real-world applications.

Requirements

• Proven track record of fine-tuning LLMs on proprietary datasets.
• Strong grasp of NLP, deep learning, and machine learning fundamentals.
• Hands-on expertise with fine-tuning strategies and evaluation methodologies.
• Strong analytical and problem-solving skills, especially in benchmarking and error analysis.
• Ability to communicate complex technical concepts to both technical and non-technical stakeholders.
• Active awareness of the latest AI research and industry developments.

Technical Skills

• Programming: Python (advanced).
• Frameworks: PyTorch or TensorFlow; Hugging Face Transformers.
• Data Tools: Pandas, NumPy, and related preprocessing libraries.
• Version Control: Git (collaborative workflows).

Preferred Qualifications

• Experience with Retrieval-Augmented Generation (RAG) and GraphRAG.
• Background in reasoning models and algorithm design.
• Familiarity with broader ML/AI tools and libraries.
• Advanced degree in Computer Science, Data Science, or related discipline.
• Prior experience publishing research in AI or NLP.