Responsibilities
- Frame complex product and customer problems as applied science opportunities with clear success metrics.
- Design, build, and evaluate machine learning and AI models, algorithms, and experimentation frameworks.
- Develop robust data, training, evaluation, and inference pipelines suitable for production use.
- Conduct rigorous offline and online experiments; analyze results and communicate actionable recommendations.
- Partner with software engineers and product managers to integrate scientific solutions into products and services.
- Improve model quality, reliability, efficiency, safety, and responsible AI practices throughout the lifecycle.
- Provide technical leadership through design reviews, mentoring, and raising the scientific bar for the team.
- Stay current with relevant research and identify opportunities to apply new methods to customer needs.
Qualifications
Required Qualifications:
- Bachelor's Degree in Statistics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ years related experience (e.g., generative AI, agentic evaluation, LLM, research)
- OR Master's Degree in Statistics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., generative AI, agentic evaluation, LLM, research)
- OR Doctorate in Statistics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience (e.g., generative AI, agentic evaluation, LLM, research)
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.
- Master's Degree in Statistics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., generative AI, agentic evaluation, LLM, research)
- OR Doctorate in Statistics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience(e.g., generative AI, agentic evaluation, LLM, research)
- OR equivalent experience.
- Experience building, deploying, and operating production machine learning systems at scale.
- Experience with deep learning, generative AI, large language models, natural language processing, recommender systems, computer vision, or another area relevant to the hiring team.
- Experience with responsible AI, model safety, privacy, fairness, robustness, and evaluation.
- Strong written and verbal communication skills, including communicating technical results to diverse stakeholders.
- Evidence of technical leadership through mentoring, cross-team collaboration, patents, or publications.
- Experience in Privacy-Preserving ML, Synthetic Data Generation, and LLM/Agentic Evaluation would be valuable.
Applied Sciences IC4 - The typical base pay range for this role across the U.S. is USD $119,800 - $234,700 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 - $261,000 per year.
Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:
https://careers.microsoft.com/us/en/us-corporate-pay
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
- Bachelor's degree in Statistics, Computer Science, Electrical Engineering, Computer Engineering, or a related field and 4+ years of related experience
- Master's degree in Statistics, Computer Science, Electrical Engineering, Computer Engineering, or a related field and 3+ years of related experience
- Doctorate in Statistics, Computer Science, Electrical Engineering, Computer Engineering, or a related field and 1+ year of related experience
- Ability to meet Microsoft, customer, and/or government security screening requirements
- Pass the Microsoft Cloud Background Check upon hire or transfer and every two years thereafter
- Master's degree in a relevant field and 6+ years of related experience
- Doctorate in a relevant field and 3+ years of related experience
- Equivalent experience
- Experience building, deploying, and operating production machine learning systems at scale
- Experience with deep learning, generative AI, large language models, natural language processing, recommender systems, computer vision, or a related area
- Experience with responsible AI, model safety, privacy, fairness, robustness, and evaluation
- Strong written and verbal communication skills
- Evidence of technical leadership through mentoring, cross-team collaboration, patents, or publications
- Experience with privacy-preserving machine learning, synthetic data generation, and LLM or agentic evaluation
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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Healthcare Strength — Health coverage is described as comprehensive, with preventive care coverage, vision options, and annual out-of-pocket limits. Feedback suggests medical, mental-health, and disability support are a major strength of the package.
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Parental & Family Support — Family support is expansive, including parental leave, family caregiver leave, child-care assistance, family concierge services, fertility options, and college-advising support for eligible employees. Feedback suggests these benefits meaningfully ease caregiving and family planning demands.
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Wellbeing & Lifestyle Benefits — Wellbeing resources include counseling and employee-assistance services, wellness reimbursements, product discounts, and charitable-matching programs. Feedback suggests these extras complement core benefits and support day-to-day quality of life.
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.
