Senior Applied Scientist

Microsoft Microsoft · Big Tech · Redmond, WA +2 · Applied Sciences

This role focuses on designing, training, and improving large-scale machine learning models for Bing Search relevance and ranking, leveraging LLMs for various understanding and summarization tasks. The goal is to deliver high-quality, low-latency search results at a global scale, involving end-to-end model development and optimization of multi-stage ranking stacks.

What you'd actually do

  1. Design, train, and improve large-scale machine learning models for Bing Search relevance and ranking, with a focus on transformer-based and LLM-powered approaches.
  2. Own end-to-end model development, including problem formulation, feature design, training, offline evaluation, and online A/B experimentation.
  3. Develop and optimize multi-stage ranking stacks (recall, coarse ranking, fine ranking) to deliver high-quality, low-latency search results at global scale.
  4. Leverage LLMs for query and document understanding, summarization, representation learning, and grounding to enhance ranking quality.
  5. Address cold-start and sparse-data challenges through content understanding, pre-training, and representation sharing.

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
  • Experience building and improving large scale Machine Learning system for search, ads, and recommendation.
  • Research background on Machine Learning, LLM and NLP.
  • Fantastic problem solver: ability to identify and solve problems that the world has not solved before.
  • 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.

What the JD emphasized

  • large-scale machine learning models
  • LLM-powered approaches
  • end-to-end model development
  • low-latency search results
  • global scale

Other signals

  • large-scale machine learning models
  • LLM-powered approaches
  • end-to-end model development
  • low-latency search results
  • global scale