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Overview

Copilot Tuning is a new product that aims to fine-tune large language models (LLMs) on tenant data, enabling task-specific agents and solutions. We are a small, nimble team that is advancing the state of the art of models in M365 Copilot. Come join our team and help transform the LLM experience in the enterprise.

We are seeking **Senior Applied Scientists and Principal Applied Scientists** **(Multiple Positions)** with strong research skills and the desire to pursue the cutting edge in model development that pushes technological boundaries. We are looking for candidates with interest and experience in language model training, data pipelines, and shipping high-quality models, willing to delve deep with customer data and generalize the learnings for the broader product.

We provide a nurturing environment to support passionate researchers and engineers in technology innovation. We seek candidates that excel in deep thinking, advanced development, and fast-paced entrepreneurial execution in a collaborative setting.

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

+ Write and execute training pipelines for large language models post-training.

+ Design experiments to show the effectiveness of LLM-based solutions.

+ Design and implement inference solutions that incorporate post-trained models following product specifications and work with broader team to ship these solutions to customers.

+ Document experiments and communicate results across the team.

+ Mentor early in career team members.

Qualifications

Required Qualifications:

+ Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 4+ 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 3+ years related experience (e.g., statistics, predictive analytics, research)

+ OR Doctorate 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 equivalent experience.

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.

Preferred Qualifications:

+ Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ 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 4+ years related experience (e.g., statistics, predictive analytics, research)

+ OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research)

+ OR equivalent experience.

+ 2+ years of experience training/fine tuning AI/ML models, preferably LLMs/SLMs (small learning model).

+ 2+ years of experience with Python and/or ML frameworks such as PyTorch.

+ 4+ years experience creating publications (e.g., patents, libraries, peer-reviewed academic papers).

+ 2+ years experience presenting at conferences or other events in the outside research/industry community as an invited speaker.

+ 2+ years of experience building Generative AI pipelines, e.g. with RAG (Retrieval augmented generation).

\#m365core #copilottuning

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 $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

Applied Sciences 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. (https://careers.microsoft.com/v2/global/en/accessibility.html)