Senior Applied Scientist

Microsoft Microsoft · Big Tech · Redmond, WA +1 · Applied Sciences

Senior Applied Scientist role focused on fine-tuning large language models (LLMs) for task-specific agents within M365 Copilot. The role involves writing and executing training pipelines, designing experiments for LLM effectiveness, and implementing inference solutions for shipping to customers. Experience in language model training, data pipelines, and generalization from customer data is key. The position also involves mentoring junior team members.

What you'd actually do

  1. Write and execute training pipelines for large language models post-training.
  2. Design experiments to show the effectiveness of LLM (large language model)-based solutions.
  3. Design and implement inference solutions that incorporate post-trained models following product specifications and work with broader team to ship these solutions to customers.
  4. Document experiments and communicate results across the team.
  5. Mentor early in career team members.

Skills

Required

  • Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience
  • Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience
  • Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience
  • equivalent experience

Nice to have

  • Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience
  • Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience
  • equivalent experience
  • 3+ years 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
  • 3+ years experience conducting research as part of a research program (in academic or industry settings)
  • 1+ year(s) experience developing and deploying live production systems, as part of a product team
  • 1+ year(s) experience developing and deploying products or systems at multiple points in the product cycle from ideation to shipping
  • 2+ years of experience training/fine tuning AI/ML models, preferably LLMs/SLMs (small language model)
  • 2+ years of experience in reinforcement learning or equivalent training techniques
  • 2+ years of experience with Python and/or ML frameworks such as PyTorch

What the JD emphasized

  • fine-tune large language models
  • task-specific agents
  • models in M365 Copilot
  • model development
  • language model training
  • shipping high-quality models
  • customer data
  • generalize the learnings
  • training pipelines for large language models post-training
  • effectiveness of LLM-based solutions
  • inference solutions that incorporate post-trained models
  • ship these solutions to customers
  • reinforcement learning

Other signals

  • fine-tune large language models
  • task-specific agents
  • models in M365 Copilot
  • model development
  • language model training
  • shipping high-quality models
  • customer data
  • generalize the learnings
  • training pipelines for large language models post-training
  • effectiveness of LLM-based solutions
  • inference solutions that incorporate post-trained models
  • ship these solutions to customers
  • reinforcement learning