Principal Applied Scientist (AI)

TL;DR

Principal Applied Scientist (AI): Leading the science behind content quality understanding and recommendation systems, combining LLMs, multimodal models, and large-scale recommender systems to drive gains in engagement, satisfaction, and trust. Focus on reducing misinformation/toxicity error rates and scaling end-to-end ML systems for a large user base.

Location: Expected to work from the office at least four days per week if living 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, balancing user satisfaction, content quality, and business goals.
• Own evaluation and experimentation by 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, distributed training/inference, and automated rollout/rollback.
• Mentor & influence by providing technical leadership across problem framing, methodology selection, code quality, and publishing/knowledge-sharing.

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; familiarity with counterfactual learning and multi‑objective optimization.
• Experience building content integrity/safety systems (e.g., misinformation, harmful content, low‑quality/duplicate detection) and quality‑aware ranking.
• Demonstrated ability to lead cross‑disciplinary efforts (PM, ENG, UXR, editorial/policy) 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 (e.g. 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).

Culture & Benefits

• Growth mindset, innovate to empower others, and collaborate to realize our shared goals.
• Culture of inclusion where everyone can thrive at work and beyond.