Microsoft Ads powers one of the world’s largest digital advertising ecosystems, delivering billions of recommendations every day. We are seeking a Senior Applied Scientist who is passionate about advancing both frontier research and real-world product impact across our ad retrieval, matching, ranking, and generation systems.
In this role, you will drive innovation at the intersection of science and product, developing novel machine learning and AI approaches while ensuring they translate into measurable improvements for customers and the business. You will leverage and advance LLMs, SLMs, LRMs, and other state-of-the-art technologies to solve challenging problems at web scale. Your work will directly influence how ads are discovered, matched, ranked, and generated, improving user experience, advertiser ROI, and the efficiency of the Microsoft Ads platform.
We are looking for a scientist who values both deep research and practical execution. You are excited by scientific exploration, but equally motivated by shipping solutions, measuring impact, and iterating based on real-world outcomes. You thrive in collaborative, cross-functional environments and enjoy turning cutting-edge ideas into production systems that serve billions of requests.
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.
Responsibilities
- Advance research and development across retrieval, ranking, matching, and generative models.
- Leverage and improve SLMs/LLMs:/LRMs train, fine-tune, and align models and productionize them.
- Evolve the Ads ranking platform toward better usability, reliability, scalability, efficiency, and architectural coherence.
- Provide technical leadership on projects: set direction, coach a distributed team, and influence cross-org strategy.
- Follow research trends in AI to guide the group keep solutions state-of-the-art. - Collaborate with research and engineering teams.
Qualifications
Required/Minimum Qualifications:
- 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.
Other Requirements: 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.
Preferred Qualifications:
- Master'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 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.
- 6+ years of experience in ML with a proven record of shipping large-scale models to production.
- Expertise in training and inference optimization.
- Proven ability to influence platform architecture and align cross-team roadmaps.
- Track record of publications in tier-1 venues such as NeurIPS, ICML, KDD, WWW, ACL, SIGIR.
- 5+ years of experience in ML with a proven record of shipping large-scale models to production. - Hands-on experience with SLM/LLM /LRM training, fine-tuning, and post-training.
- Experience designing and scaling recommendation systems with massive query/item spaces and multi-stage ranking pipelines.
- Proficiency with deep learning frameworks (e.g., PyTorch, Hugging Face, TensorFlow) and distributed training on large datasets.
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.
Skills Required
- Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field with required experience (Bachelor's +4 years OR Master's +3 years OR Doctorate +1 year) OR equivalent experience.
- Ability to meet Microsoft, customer, and/or government security screening requirements, including passing the Microsoft Cloud background check upon hire and every two years.
- 6+ years of ML experience with a proven record of shipping large-scale models to production.
- Expertise in training and inference optimization, and experience with distributed training on large datasets.
- Hands-on experience training, fine-tuning, and post-training alignment of SLMs/LLMs/LRMs.
- Experience designing and scaling recommendation systems with massive query/item spaces and multi-stage ranking pipelines.
- Proficiency with deep learning frameworks (PyTorch, Hugging Face, TensorFlow) and distributed training.
- Proven ability to influence platform architecture and align cross-team roadmaps; track record of publications in tier-1 ML/IR venues.
Microsoft Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Microsoft and has not been reviewed or approved by Microsoft.
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Fair & Transparent Compensation — Pay is presented as broadly competitive overall, with clear role/level/location variation and an emphasis on using posted ranges and band information for apples-to-apples comparisons.
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Retirement Support — Retirement benefits are described as a standout, highlighted by a strong 401(k) match structure and immediate vesting, plus additional plan features for tax-advantaged saving.
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Parental & Family Support — Family-oriented benefits are portrayed as a meaningful strength, with substantial paid parental leave and added supports like back-up care and adoption/surrogacy assistance.
Microsoft Insights
What We Do
At Microsoft, our mission is to empower every person and every organization on the planet to achieve more. Our mission is grounded in both the world in which we live and the future we strive to create. Today, we live in a mobile-first, cloud-first world, and the transformation we are driving across our businesses is designed to enable Microsoft and our customers to thrive in this world.
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