Data Scientist - Language Model Fine-Tuning Specialist

Role: Data Scientist - Language Model Fine-Tuning Specialist

Years of exp: 6+ Years

Location: Remote 

 

Job Description:

We are seeking a highly skilled Data Scientist with expertise in fine-tuning LLM/SLM 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 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.

· 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.

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.