TL;DR

Principal Applied Scientist (AI): Leading the science behind ranking and content-quality combining LLMs, multimodal models, and large-scale recommender systems. Focus on safety and trust, translate user engagements and behavioral history into model objectives and product bets.

Location: Expected to work from the office at least four days per week within a 50- mile commute of a designated Microsoft office in the U.S.

Salary: USD $139,900 – $304,200 per year.

Company

Microsoft’s mission is to empower every person and every organization on the planet to achieve more.

What you will do

Lead content‑quality understanding at scale by designing and deploying models that assess credibility, usefulness, freshness, safety, and diversity across modalities.
Advance the recommendation & ranking stack by architecting and productionizing large‑scale DNN/LLM‑enhanced recommenders.
Own evaluation and experimentation, defining offline metrics and online methodologies to confidently attribute impact and guard against regressions.
Champion safety & trust by partnering with policy and platform teams to encode safety standards and editorial principles into the ML system.
Scale E2E ML systems by collaborating with engineering on data contracts, feature stores, and distributed training/inference.
Mentor & influence peers through design reviews, deep‑dives, and principled decision-making.

Requirements

Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience.
OR Master’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience.
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience.
Experience with LLMs (prompting, finetuning, RAG), multimodal modeling, and retrieval‑augmented recommendation.
Demonstrated ability to lead cross‑disciplinary efforts from idea to shipped impact; mentoring scientists and setting technical vision.

Nice to have

Master’s Degree in Computer Science, Electrical or Computer Engineering, or related field AND 9+ years related experience in machine learning, deep learning or similar technologies.
Publications at top AI/ML conferences (e.g., KDD, SIGIR, EMNLP, NIPS, ICML, ICLR, RecSys, ACL, CIKM, CVPR, ICCV, etc.).
Familiarity with Microsoft stack (e.g., Azure ML, Kusto, Synapse, Azure AI Foundry).
Experience working with recommender systems/ranking or content‑quality/safety models at consumer scale, with clear business impact.
Experience in Python and at least one major deep learning framework (PyTorch/TensorFlow) with large‑scale data processing and training/inference on distributed systems.
Experience in evaluation & experimentation (offline metrics, A/B testing, bandits) and ML model development lifecycle.

Culture & Benefits

Microsoft is an equal opportunity employer.