Applied Scientist 2

at  Microsoft

Join the dynamic Microsoft Mobile AI team in Redmond, WA, where we’re seeking an Applied Scientist 2 to drive innovation in our cutting-edge Artificial Intellignence/ Machine Learning (AI/ML) systems.
As part of our team, you’ll collaborate with passionate engineers, data scientists, and product managers to develop advanced solutions leveraging Large Language Models (LLMs), Image Generation, Natural Language Processing (NLP), and Machine Learning models.
Together, we’re revolutionizing the landscape of AI-driven mobile applications, powering text and rich media assist features on beloved platforms like Microsoft SwiftKey.
Be part of our mission to create intelligent on-device copilot models, seamlessly blending text and rich media features to enhance your digital interactions, whether drafting a blog post, crafting a social media update, or composing a formal email.
Join us and be at the forefront of transformative technology!
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.

REQUIRED/MINIMUM QUALIFICATIONS

• Bachelor’s Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ 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 1+ year(s) related experience (e.g., statistics, predictive analytics, research)
• OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
• OR equivalent experience.
• 2+ years of hands-on experience in Data Science and ML modeling, shipped scalable models in production.

ADDITIONAL OR PREFERRED QUALIFICATIONS

• Familiarity with LLM distillation, fine-tuning.
• Responsible AI (RAI) Advocacy: Experience or understanding of ethical considerations and best practices in AI development, with a commitment to championing Responsible AI principles.
• Experience working in a research environment.
• Good understanding of deep learning and large-scale ML concepts.
  Applied Sciences IC3 - The typical base pay range for this role across the U.S. is USD $98,300 - $193,200 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 $127,200 - $208,800 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
  Microsoft will accept applications for the role until June 5, 2024.
  Microsoft is an equal opportunity employer. Consistent with applicable law, 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

• Collaborate closely with the Microsoft Copilot team, from conceptualization to implementation, to develop scalable GenAI capabilities for applications like Microsoft SwiftKey and other mobile applications.
• Continually optimize supported scenarios by implementing techniques such as distillation and fine-tuning LLMs, focusing on reducing costs and latencies. Establish and refine evaluation metrics, prioritizing accuracy, speed, and efficiency.
• Define datasets and metrics for Responsible AI (RAI) assessment and collaborate with RAI teams to ensure compliance.
• Lead project initiatives by setting clear goals and timelines, assuming ownership, and orchestrating collaborative efforts with stakeholders: Product Managers, designers and client teams, to craft top-tier AI systems that bring delight to end users through seamless delivery.
• Thrive on addressing complex challenges and adapting to emerging technologies and innovations in AI, making significant contributions to project outcomes.
• Contribute to academic and industry discourse by publishing papers, participating in conferences, and serving as a representative of Mobile AI innovation.

Other

• Embody our Culture & Values