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Machine Learning Engineer
Redmond, United States
Machine Learning Engineer
Redmond, Washington, United States
Date posted
Sep 29, 2025
Job number
1882133
Work site
Fully on-site
Travel
0-25 %
Role type
Individual Contributor
Profession
Research, Applied, & Data Sciences
Discipline
Applied Sciences
Employment type
Full-Time
Overview
Are you excited by the challenge of building intelligent, autonomous systems that deliver real-world impact? The Commerce Risk Analytics team at Microsoft is looking for a machine learning engineer to design, develop, and continuously improve a multi-agent AI Risk system that enables autonomous risk transaction review and decision-making. You’ll be working at the intersection of large language models (LLMs), applied machine learning, and platform integration—building solutions that power scenarios from fraud prevention to customer support automation.
We’re hiring across several focus areas, and your role will align with your expertise and interests:
- Autonomous Agent Development for Risk Decision – building LLM-based decision-making agents and advancing a multi-agent risk system
- AI Integration & MLOps – enabling scalable infrastructure, data pipelines, and operational excellence
- Quality & Integration – focusing on agent behavior testing, UI/UX integration, and platform reliability
Qualifications
Required Qualifications:
-
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.
- 3+ years of experience in software engineering, data science, or machine learning
- 2+ years experience with LLMs, prompt engineering, and the OpenAI API
- 2+ years experience with Azure services, cloud infrastructure, and CI/CD pipelines
Preferred Qualifications:
- Experience working with multi-agent frameworks such as AutoGen, Semantic Kernal and Langchain.
- Knowledge of MLOps practices, including containerization, infrastructure-as-code, and monitoring
- Exposure to Power Platform, Microsoft Graph API, or enterprise integration technologies
- Experience debugging skills and a solid understanding of security and data protection principles
- Ability to communicate technical concepts effectively with both technical and non-technical stakeholders
- Proficiency in Python for development and scripting
Applied Sciences IC3 - The typical base pay range for this role across the U.S. is USD $100,600 - $199,000 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 $131,400 - $215,400 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
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
Microsoft will accept applications for the role until October 13th, 2025
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.
Responsibilities
As a machine learning engineer, you will:
- Design and optimize multi-agent AI architectures that enable autonomous risk assessment and decision-making at scale, leveraging agent collaboration to reduce huma manual effort and minimize false positive rates.
- Implement agentic ML infrastructure that automates the full model development lifecycle enabling continuous learning, adaptive optimization, and scalable risk decisioning.
- Build and evolve AI-driven solutions that improve the accuracy, speed, and adaptability of fraud detection across a wide range of Commerce scenarios.
- Develop infrastructure and MLOps pipelines to support continuous training, deployment, and monitoring
- Conduct rigorous behavior testing and validation, focusing on performance, safety, and real-world edge cases
- Integrate AI agents with Azure AI services, Microsoft Graph API, Power Platform, and internal systems
- best practices in security, compliance, and privacy to all aspects of agent development
- Partner closely with product managers, engineers, and data scientists to translate complex business challenges into scalable technical solutions, ensuring alignment and impact across stakeholders
Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.
Industry leading healthcare
Educational resources
Discounts on products and services
Savings and investments
Maternity and paternity leave
Generous time away
Giving programs
Opportunities to network and connect
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 and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.
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