Member of Technical Staff, Machine Learning, AI Platform at Microsoft

Mountain View, California, United States -

Full Time

Start Date

Immediate

Expiry Date

13 Mar, 26

Salary

234700.0

Posted On

13 Dec, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, AI Safety, Data Mining, Prompt Engineering, LLM Evaluation, Classifier Training, User Research, Safety Testing, Python, C, C++, C#, Java, JavaScript, Responsible AI, AI Alignment, Consumer Product Trust

Industry

Software Development

Description

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. Starting January 26, 2026, MAI employees are expected to work from a designated Microsoft office at least four days a week if they live within 50 miles (U.S.) or 25 miles (non-U.S., country-specific) of that location. This expectation is subject to local law and may vary by jurisdiction. 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. Qualifications Required Qualifications Bachelor's Degree in Computer Science or related technical field AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. Preferred Qualifications Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python OR equivalent experience. 1+ years' experience prompting and working with large language models. 1+ years’ experience writing production-quality Python code. Experience and/or interest in the field of Responsible AI, AI Safety & Alignment or consumer product trust & safety Experience in the field of Responsible AI, AI Safety & Alignment or consumer product trust & safety Software Engineering 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 $158,400 - $258,000 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 Software Engineering IC5 - The typical base pay range for this role across the U.S. is USD $139,900 - $274,800 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 - $304,200 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.

Responsibilities

Develop and implement safety methodologies for AI products, ensuring they align with organizational values. Create evaluation frameworks and automated safety testing systems to assess model safety across various scenarios.