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Copilot Tuning is a new product that aims to fine-tune large language models (LLMs) on tenant data, enabling task-specific agents and solutions. We are a small, nimble team that is advancing the state of the art of models in M365 Copilot. Come join our team and help transform the LLM experience in the enterprise.
Job Responsibility:
Write and execute training pipelines for large language models post-training
Design experiments to show the effectiveness of LLM-based solutions
Design and implement inference solutions that incorporate post-trained models following product specifications and work with broader team to ship these solutions to customers
Document experiments and communicate results across the team
Mentor early in career team members
Requirements:
Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 7+ years related experience (e.g., statistics predictive analytics, research)
OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ years related experience (e.g., statistics, predictive analytics, research)
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ year(s) related experience (e.g., statistics, predictive analytics, research)
OR equivalent experience
3+ years of experience training/fine tuning AI/ML models, preferably LLMs/SLMs (small learning model)
3+ years of experience with Python and/or ML frameworks such as PyTorch
Ability to meet Microsoft, customer and/or government security screening requirements are required for this role
Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter
Nice to have:
3+ years of experience creating publications (e.g., patents, libraries, peer-reviewed academic papers)
3+ years of experience presenting at conferences or other events in the outside research/industry community as an invited speaker
3+ years of experience building Generative AI pipelines, e.g. with RAG (Retrieval augmented generation)