Senior Applied Scientist - Language Understanding and Grounding Data Quality

Microsoft • Redmond, WA

2d

About The Position

We turn everyday, messy queries into precise, actionable signals that power M365 Copilot and Microsoft Search. Language understanding (LU) sits on the critical path—it can run on every query—classifying intent and slots and shaping the downstream search plan across providers in the substrate stack. Our work ensures that all tool calls are appropriately scoped and parameterized so Copilot starts with the right grounding data, improving relevance and limiting hallucinations.

As Senior Applied Scientist - Language Understanding and Grounding Data Quality, what you’ll work on

Large Language Model (LLM)/SLMpowered LU: intent & slotting with calibrated confidence, optimized for low latency and high reliability in Copilot experiences

MultiQuery (MQ) expansion: embrace ambiguity by exploring multiple interpretations and smarter fallbacks to boost recall without sacrificing precision.

Finetuning & eval tooling: Our team works to improve model quality specific to tool calling: Making sure the right tool is called in the right way at the right time to get the best grounding data possible. To do it, we post-train LLMs iterating fast with robust datasets, prompt evaluation, and shiproom discipline to raise quality week over week through leading edge fine-tuning

Global reach: help bring LU to more languages and markets with compliant modeling practices and scalable i18n strategy.

Deep partner collaboration: work side-by-side with Relevance and Reasoning on unified strategies that blend lexical + semantic retrieval.

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.

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.
• Experience in Python, C# or similar programming languages for model development, training, and evaluation
• Experience with large-scale machine learning systems, including training, fine-tuning, and deployment of LLMs or similar models
• Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include but are not limited to the following specialized security screenings: Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Nice To Haves

• Hands-on experience with prompt engineering, reinforcement learning from human feedback (RLHF), or reward modeling
• Familiarity with distributed systems and cloud platforms (e.g., Azure) for large-scale ML workloads

Responsibilities

• Improve LLM capabilities influencing grounding data quality.
• Apply latest research to post-train LLMs.
• Build and evaluate metrics and reward models.
• Add new functionality and ensure high quality for customers using Copilot on their Business data.
• Design and implement scalable evaluation pipelines for LU and grounding quality
• Collaborate with cross-functional teams to define success metrics and drive continuous improvement in Copilot experiences

What This Job Offers

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