Job Description

Member of Technical Staff - Machine Learning, AI Safety

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Zurich, Switzerland



Date posted

Sep 25, 2025

Job number

1883079

Work site

2 days / week in-office

Travel

0-25

%

Role type

Individual Contributor

Profession

Software Engineering

Discipline

Software Engineering

Employment type

Full-Time

Overview

As a Member of Technical Staff - Machine Learning, AI Safety, you will develop and implement cutting-edge safety methodologies and mitigations for products that are served to millions of users through Copilot every day. Users turn to Copilot for support in all types of endeavors, making it critical that we ensure our AI systems behave safely and align with organizational values. You may be responsible for developing new methods to evaluate LLMs, experimenting with data collection techniques, implementing safety orchestration methods and mitigations, and training content classifiers to support the Copilot experience. We're looking for outstanding individuals with experience in machine learning or machine learning infrastructure who are also strong communicators and great teammates. The right candidate takes the initiative and enjoys building world-class, trustworthy AI experiences and products in a fast-paced environment.
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.

Qualifications

Qualifications

Required Qualifications

Bachelor's Degree in Computer Science, or related technical discipline AND technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python + OR equivalent experience.
Experience prompting and working with large language models. Experience writing production-quality Python code.

Preferred Qualifications

Demonstrated interest in Responsible AI.

Responsibilities

Responsibilities

Leverage expertise to uncover potential risks and develop novel mitigation strategies, including data mining, prompt engineering, LLM evaluation, and classifier training. Create and implement comprehensive evaluation frameworks and red-teaming methodologies to assess model safety across diverse scenarios, edge cases, and potential failure modes. Build automated safety testing systems, generalize safety solutions into repeatable frameworks, and write efficient code for safety model pipelines and intervention systems. Maintain a user-oriented perspective by understanding safety needs from user perspectives, validating safety approaches through user research, and serving as a trusted advisor on AI safety matters Track advances in AI safety research, identify relevant state-of-the-art techniques, and adapt safety algorithms to drive innovation in production systems serving millions of users. Embody our culture and values.
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.