Member of Technical Staff – Machine Learning Full-time

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Overview

As a Member of Technical Staff – Machine Learning, you will work on the Technical Safety squad to ensure that Copilot’s messages comply with content policies and the larger values of the organization. You may be responsible for developing new methods to evaluate LLMs, experimenting with data collection techniques for safety post-training, or training content classifiers to support the Copilot experience.?We’re?looking for someone with experience in data science and machine learning, but also a strong communicator and great teammate.?The right candidate takes the initiative and enjoys building world-class consumer 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.

Responsibilities

• Leverage subject matter expertise to uncover and mitigate safety issues in consumer Copilot.
• Oversee data acquisition or generation efforts, ensuring that the data meets product needs.
• Generalize machine learning (ML) solutions into repeatable frameworks.
• Conduct thorough review of data analysis and techniques used to summarize the process review and highlight areas that have been missed or need reexamining.
• Track advances in industry and academia, identifies relevant state-of-the-art research, and adapts algorithms and/or techniques to drive innovation and develop new solutions.
• Independently write efficient, readable, extensible code and model pipelines.
• Contribute to defining the safety roadmap for Copilot, keeping in mind business and product goals.
• Commit to a customer-oriented focus by acknowledging customer needs and perspectives, validating customer perspectives, focusing on broader customer context, and serving as a trusted advisor.

Qualifications

Required Qualifications:

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 1 year(s) data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR Master’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 3 years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR Bachelor’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 5 years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR equivalent experience.
• Experience prompting and working with large language models.
• Experience writing production-quality Python code.

Preferred Qualifications:

• Doctorate in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 8 years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR Master’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 10 years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR Bachelor’s Degree in Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, Computer Science, or related field AND 12 years data-science experience (e.g., managing structured and unstructured data, applying statistical techniques and reporting results)
• OR equivalent experience.
• Demonstrated interest in Responsible AI.

Data Science IC4 – The typical base pay range for this role across the U.S. is USD $117,200 – $229,200 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 $153,600 – $250,200 per year.

Data Science IC5 – The typical base pay range for this role across the U.S. is USD $137,600 – $267,000 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 $180,400 – $294,000 per year.

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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 and processes offers for these roles on an ongoing basis.

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