Applied Scientist II / Senior Applied Scientist at Microsoft

Boston, Massachusetts, United States -

Full Time

Start Date

Immediate

Expiry Date

20 Mar, 26

Salary

199000.0

Posted On

20 Dec, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, NLP, Deep Learning, Python, C#, PyTorch, Triton, Data Processing, Feature Design, Model Development, Evaluation, Deployment, Unit Testing, Test Driven Development, DevOps, API Design, Data Analysis

Industry

Software Development

Description

Overview The CoreAI Platform and Tools organization is building transformative experiences that leverage the latest AI technology while upholding Microsoft’s commitment to ethical and responsible standards for Artificial Intelligence. The Responsible AI (RAI) service components you build will be accessed by hundreds of millions of consumers across the globe and will touch all facets of Artificial Intelligence. The Responsible AI team within this division is looking for an experienced Applied Scientist II and a Senior Applied Scientist with a proven track record to help tackle the challenges of enabling customers to leverage the latest advancements in AI responsibly. Responsibilities Conduct supervised fine-tuning of LLMs, applying Reinforcement Learning from Human Feedback in the process, and conducting thorough evaluation of those. Work with tech lead on the design and implementation of Agent adversarial evaluations and safety mitigations, enabling agent creators to identify potential risks and apply appropriate safeguards to ensure the safety and security of Agents. You will collaborate closely with the Responsible AI engineering team to deliver these mitigations at scale for Responsible AI customers, refine existing implementations based on operational performance, and troubleshoot and resolve end-to-end issues. Qualifications Required Qualifications: Bachelor's Degree in Computer Science, Computational Linguistics, or related field AND 2+ years related experience (e.g., statistics, predictive analytics, research) OR Master's Degree in Computer Science, Computational Linguistics, or related field AND 1+ year(s) related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Computer Science, Computational Linguistics, or related field 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: Master's Degree in Computer Science, Computational Linguistics, related field AND 6+ years related experience (e.g., statistics, predictive analytics, research) OR Doctorate in Computer Science, Computational Linguistics, or related field AND 3+ years related experience (e.g., statistics, predictive analytics, research) OR equivalent experience. 2+ years of science experience owning feature design, model development, evaluation and deployment. 3+ years of science experience owning feature design, model development, evaluation and deployment. Full stack (client-to-service) development experience is a plus. Rich experience in machine learning, particularly in NLP and deep learning. Experience with language model training and evaluation is a big plus. Experience with research in Responsible AI is a big plus. Proficiency in programming languages such as Python, C#, and familiarity with machine learning frameworks including PyTorch and Triton. Experience with data processing and handling large datasets. Experience in engineering methodologies: Unit testing, Test Driven Development, DevOps, and a firm commitment to quality. Solid platform/API design, debugging and data analysis skills. Ability to work collaboratively in a team and communicate complex concepts effectively. #coreai 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 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 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

Conduct supervised fine-tuning of LLMs and evaluate them. Collaborate with the Responsible AI engineering team to deliver safety mitigations at scale.