Applied Scientist II

Microsoft • Redmond, WA

1d • Hybrid

About The Position

Are you interested in solving large‑scale search problems and building next‑generation of Query Understanding solutions powered by LLMs and SLMs? If yes, the Bing Orca team is for you!
The Orca team is a research‑driven applied science and engineering group building the next generation of efficient, scalable, and highly capable AI models. Our mission is to push the boundaries of model reasoning, compression, and alignment—making advanced intelligence accessible, reliable, and cost‑effective across Microsoft’s ecosystem.
We’re known for pioneering techniques that help compact models learn rich reasoning abilities from frontier‑scale teachers. But we don’t stop at research: we also own the end‑to‑end infrastructure, tooling, and runtime systems that bring these models to life in production.
Our work spans deep research, large‑scale engineering, and real‑world product impact:
Advanced Model Research
Develop novel distillation and compression methods
Explore chain‑of‑thought, multi‑step reasoning, and structured supervision
Build evaluation frameworks that measure reasoning, robustness, and safety
Production‑Grade Infrastructure & Hosting
Own the full model‑serving stack for Orca models
Build high‑performance inference pipelines optimized for latency, throughput, and cost
Maintain high availability, stability, and reliability across global deployments
Design scalable systems that support rapid experimentation and safe rollout of new model variants
Training & Experimentation at Scale
Run large‑scale training jobs and ablation studies
Develop internal tools that accelerate research velocity
Collaborate with platform teams to optimize compute efficiency
Real‑World Impact
Our systems & models serve users in 100+ markets worldwide, handling 100M+ queries and interactions every day.
We are hiring an Applied Scientist II to join our world of search retrieval, ranking, relevance optimization, driving real user impact in production systems at global scale.
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 2+ 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 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field OR equivalent experience.
• Ability to collaborate effectively in a fast‑paced research and engineering environment.
• Solid problem‑solving skills and eagerness to learn new methods, tools, and systems.
• Solid ability to translate research ideas into reliable, maintainable code.
• Demonstrated ability to work effectively with cross‑functional teams, including researchers, engineers, and product partners.

Nice To Haves

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 5+ 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.
• Experience training, fine‑tuning, and evaluating small or efficient language models (SLMs) at scale.
• Familiarity with PyTorch or TensorFlow and common ML tooling
• Experience with Search and Query Understanding, including ranking models, retrieval pipelines, relevance evaluation, or semantic understanding of queries is a huge plus.

Responsibilities

• Develop, train, and evaluate machine learning models with guidance from senior scientists.
• Implement model improvements through experimentation, data analysis, and iterative refinement.
• Contribute to the team’s core codebase, including training pipelines, evaluation tools, and automation.
• Build and maintain tooling that improves research velocity, experiment tracking, and model debugging.
• Support the development and operation of model‑serving infrastructure with a focus on reliability and performance.
• Collaborate with engineers and researchers to bring models from prototype to production‑ready systems.
• Participate in code reviews, documentation, and best‑practice engineering processes.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees