Document experiments and communicate results across the team. Mentor early in career team members.
Responsibilities
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.
Required Qualifications
Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. Experience training/fine tuning AI/ML models, preferably LLMs/SLMs (small learning model). Experience with Python and/or ML frameworks such as PyTorch. Experience creating publications (e.g., patents, libraries, peer-reviewed academic papers). Experience presenting at conferences or other events in the outside research/industry community as an invited speaker. Experience building Generative AI pipelines, e.g. with RAG (Retrieval augmented generation).
Original Posting
This role is sourced from Microsoft. Apply on Microsoft careers page