Senior Applied Scientist & Principal Applied Scientist (Multiple Positions)

Microsoft

14d

About The Position

Senior Applied Scientist and Principal Applied Scientist (Multiple Positions) -Microsoft Applied Sciences Group
From being able to log you in with face recognition, correct your gaze during a video chat to maintain eye contact, to the exciting possibilities in augmented reality, are you itching to play a part in bringing applications of machine learning to millions of users?

The Microsoft Applied Sciences Group incubates disruptive technologies for Microsoft’s next-gen hardware products and is working on several exciting projects that will shape how computers and other devices perceive the user and the user’s environment. Operating as a startup within the company, this team works closely with several research and product teams to bring compelling new experiences to the market. A lot of these experiences will be powered by machine learning – and as part of this team, you will have the unique opportunity to work on almost every aspect of a shipping vision system: camera optics, sensors, data pipeline and of course, developing and implementing the algorithms that make magic happen!

The team is growing, and we have an exciting opportunity for talented Senior Applied Scientist and Principal Applied Scientist to drive and lead implementation of state-of-the-art AI algorithms for specific and general-purpose silicon on next generation devices and operating systems. This is a hands-on team lead task. You will have collaboration opportunities throughout the organization and will be building new stuff that really works and has millions of users.
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.

Requirements

• 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.
• Ability to meet Microsoft, customer and/or government security screening requirements are required for this role.
• Microsoft Cloud Background Check: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

Nice To Haves

• Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 9+ years related experience (e.g., statistics, predictive analytics, research)
• OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 6+ years related experience (e.g., statistics, predictive analytics, research)
• OR equivalent experience.
• 3+ years of experience in deep learning and large language models, including transformer‑based architectures (e.g., BERT, GPT‑2/GPT‑3, LLaMA, OPT).
• 3+ years of experience optimizing large language models, including model compression, distillation, quantization, and parameter‑efficient fine‑tuning techniques (e.g., LoRA, GPTQ).
• Proficiency in Python for machine learning, research, and experimentation workflows.
• Experience with modern ML frameworks such as PyTorch or TensorFlow.
• Experience with dataset curation, data generation using state‑of‑the‑art LLM prompting techniques, and automated model evaluation.
• Experience with model conversion and deployment frameworks (e.g., ONNX).
• Demonstrated record of publications in top‑tier conferences or journals (e.g., NeurIPS, ICML, ICLR, ACL, CVPR, ICCV, ECCV, TPAMI).
• Experience building production‑quality APIs, SDKs, or software packages for third‑party or external consumption.
• Demonstrated ability and passion for incubating new ideas, solving complex problems, and building working systems.

Responsibilities

• Optimize, fine tune and transform models for edge device inferencing.
• Contribute to the technical design, architecture, development, and evaluation of DNN models.
• Collaborate with engineering and product development teams.
• Contribute to a real-time system involving multiple components.
• Assist in identifying and addressing issues in ML frameworks and associated hardware.
• Mentor junior engineers and contribute to team knowledge-sharing sessions.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level