Senior Data Scientist - fine-tuning language models must have

We are seeking a highly skilled Data Scientist with expertise in fine-tuning language models using proprietary company data. The ideal candidate will have a strong background in data preparation, model fine-tuning, and benchmarking, as well as staying updated on the latest advancements in the AI field.

Key Responsibilities:

• Develop and prepare datasets for language model fine-tuning using proprietary data.
• Fine-tune language models using techniques such as LoRA, QLoRA, and GRPO.
• Benchmark model performance and analyze results to ensure optimal outcomes.
• Deploy fine-tuned model for inference
• Stay current with the latest research and innovations in language modeling, including relevant arXiv papers.
• Collaborate with cross-functional teams to integrate fine-tuned models into products and services.

Requirements:

• Proven experience in fine-tuning language models with proprietary datasets.
• Proficiency in advanced fine-tuning techniques and methodologies.
• Strong analytical skills for benchmarking model performance.
• Up-to-date knowledge of recent research papers and developments in the field.
• Excellent communication skills and ability to collaborate with technical and non-technical stakeholders.
• Strong background in ML, NLP and Deep Learning

Required Tools and Technologies:

• Proficiency in Python programming.
• Experience with machine learning frameworks such as TensorFlow or PyTorch.
• Familiarity with Hugging Face Transformers for language model manipulation.
• Knowledge of data processing and manipulation libraries, such as Pandas and NumPy.
• Experience with version control systems like Git.

Preferred Qualifications:

• Experience with Relevance-Augmented Generation (RAG) and GraphRAG frameworks.
• Experience with reasoning models and algorithm development.
• Familiarity with additional machine learning tools and libraries.
• Advanced degree in Computer Science, Data Science, or related field.
• Having prior experience publishing research paper on AI field.

Start date: ASAP

Remote vs Onsite: Remotely

US Hours overlap needed?: Minimum 2-6pm CET, preferred 2-7pm CET