Senior Applied Scientist

Microsoft•Redmond, WA

1d•Hybrid

About The Position

You’re driven by the thrill of solving problems no one has cracked yet—and you want your work to shape how billions of people search, discover, and understand information. In MAI, you’ll join a team pushing the boundaries of LLM post‑training, alignment, next‑generation search, and the evolving RAG stack. You’ll work alongside researchers and engineers who share your appetite for innovation and your desire to build systems that are more accurate, more aligned, and more useful to the world. As an Applied Scientist, you will design, experiment with, and refine advanced post‑training and alignment techniques that elevate the reasoning, safety, and retrieval capabilities of large language models. You’ll architect and optimize next‑generation search pipelines, develop cutting‑edge RAG methodologies, and translate research breakthroughs into production‑ready systems that power real user experiences. This opportunity will allow you to accelerate your career growth, deepen your expertise in large‑scale AI systems, and sharpen your ability to drive research into impactful product innovation. Flexible work options are available, including partial remote work depending on team needs. Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees, we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond. Starting January 26, 2026, Microsoft AI (MAI) employees who live within a 50- mile commute of a designated Microsoft office in the U.S. or 25-mile commute of a non-U.S., country-specific location are expected to work from the office at least four days per week. This expectation is subject to local law and may vary by jurisdiction.

Requirements

Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., statistics predictive analytics, research).
OR 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.

Nice To Haves

Master's Degree in Statistics, Econometrics, Computer Science, Electrical OR Computer Engineering, OR related field AND 6+ years related experience (e.g., statistics, predictive analytics, research).
OR Doctorate in Statistics, Econometrics, Computer Science, Electrical OR Computer Engineering, OR related field AND 3+ years related experience (e.g., statistics, predictive analytics, research).
OR 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.

Responsibilities

You will master one or more subareas and build expertise across a broad research landscape, including advanced research methodologies and applied techniques. You’ll develop deep knowledge of a service, platform, or domain, and identify product opportunities by sharing emerging industry trends and applied technologies.
You will review business requirements and incorporate research insights to meet strategic goals. You’ll provide direction on the types of data needed to solve complex problems and apply deep subject‑matter expertise to drive measurable business impact.
You will support the onboarding of junior team members and help develop academic collaborators into effective contributors within multidisciplinary teams. You’ll identify promising research talent, engage with the academic community, and strengthen Microsoft’s long‑term recruiting pipeline.
You will document ongoing work, experimental results, and research findings to promote transparency and innovation. You’ll also apply your understanding of fairness and bias to help shape ethics and privacy policies related to research processes and data collection.
You will advance LLM post‑training and alignment techniques by designing, implementing, and evaluating novel methods that improve reasoning quality, safety, controllability, and factual grounding across large‑scale models.
You will develop next‑generation search capabilities by building and optimizing retrieval, ranking, and relevance systems that integrate deeply with LLM‑powered experiences.
You will architect and refine RAG pipelines that enhance retrieval fidelity, reduce hallucinations, and deliver more context‑aware, user‑aligned responses in production environments.
You will translate research into production by running experiments, analyzing results, and collaborating with engineering partners to deploy scalable, reliable model improvements.
You will drive scientific rigor through hypothesis‑driven experimentation, reproducible methodologies, and clear documentation of findings, insights, and model behaviors.
You will collaborate across disciplines—including research, engineering, product, and design—to shape long‑term strategy for search, alignment, and retrieval‑augmented systems.
You will monitor and evaluate model performance using quantitative metrics, qualitative assessments, and user‑centric evaluation frameworks to ensure continuous improvement.
You will contribute to a culture of innovation by sharing learnings, mentoring peers, and participating in internal research discussions, reviews, and technical deep dives.