Data Scientist

Overview

We'relooking for data scientists to help build the next generation of post-training methods for frontier models at Microsoft AI.You'lljoin a small, high-impact team working across all stages of post-training, with a focus onevaluation design, high-quality training data, and scalable data pipelinesforstate-of-the-artfoundation models.

In this role,you'llhelp turn raw model capability intoreliable, aligned, and measurable performance improvements, directly shaping how frontier models behave in real-world deployments.

About the Role:

Microsoft AI is building the next generation of frontier models that power Copilot and other large-scale AI experiences. ThePost-Trainingteamis responsible fortransforming powerful pretrained models intorobust, aligned, and high-performing systemsused by millions of people worldwide.

Our work focuses on improvinggeneral quality, instruction following, coding and math ability, tool use, agentic behaviors, personality, and other critical model capabilities. Weoperateacross the full post-training lifecycle - fromdata generation and curation, toevaluation and diagnostics, toreward modeling and reinforcement learning.

We are a small, highly autonomous team that works closely with pre-training, product, and engineering partners to rapidly iterate on ideas, run large-scale experiments, and safely advance model capabilities. Each team member owns meaningful parts of the post-training pipeline and has direct access to thecompute, data, and decision-making needed to move quickly from insight to production.

Microsoft Superintelligence Team

This role is part of Microsoft AI's Superintelligence Team. The MAIST is astartup-like team inside Microsoft AI, created to push the boundaries of AI towardHumanist Superintelligence-ultra-capable systems thatremaincontrollable, safety-aligned, and anchored to human values.Our mission is to create AI that amplifies human potential while ensuring humanityremainsfirmly in control. We aim to deliver breakthroughs thatbenefitsociety-advancing science, education, and global well-being.

We're also fortunate to partner with incredible productteamsgiving our models the chance to reach billions of users and createimmensepositive impact. Ifyou'rea brilliant, highly-ambitiousand low ego individual,you'llfit right in-come and join us as we work on our next generation of models! Responsibilities

• Design evaluations of advanced model capabilities and use them to drive rapid, high-signal iteration loops

• Work with vendors to produce high quality evaluation and training data

• Build data pipelines to produce high quality evaluation and training data

• Build data flywheels to hill-climb on model weaknesses, using data from various surfaces where our models are deployed

• Ensureoptimalquality,quantityand coverage of data across our post-training stages

• Run post-training experiments and ablations to produce models that climb ourevals

• Embody ourcultureandvalues.

We'reLookingForPeople Who:

• Havedeep experience withLLMs, either training them or applying them in production

• Have developed production-scale data pipelines for synthesizing, curating, or processinglargequantitiesof data

• Can design, run, and interpret large-scale ML experiments with careful statistical and empirical reasoning.

• Possess strong generalist engineering and mathematical skills.

• Have clear written and verbal communication, and theability to collaborate effectively withresearchers,engineersand other disciplines.

• Bonus skills:Demonstrated SOTA results in any area of large-scale training, inference, or evaluation.

Qualifications
Required skills Handson experience with large language models, including training or applying them in production (not just prompting) Designing and running posttraining experiments (evals, ablations, preference tuning / RLHFstyle methods) Building and owning scalable data pipelines for training and evaluation data Strong Python skills for ML experimentation, data processing, and analysis Solid statistical, experimental, and general engineering fundamentals

Software Engineering IC4 - The typical base pay range for this role across the U.S. is USD $119,800.00 - $234,700.00 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $160,200.00 - $261,000.00 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $142,800.00 - $274,800.00 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $188,000.00 - $304,200.00 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.