Applied Scientist II and Senior Applied Scientists (Multiple Positions)-Microsoft Applied Sciences Group

Applied Scientist II and Senior Applied Scientists (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 Applied Scientist II and Senior Applied Scientists (Multiple Positions) 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.

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.

Qualifications

Required Qualifications: 

• Bachelor's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 2+ years related experience with Machine Learning (ML), Natural Language Processing (NLP), Large Language Models (LLM).
  • OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ year(s) related experience with Machine Learning (ML), Natural Language Processing (NLP), Large Language Models (LLM).
  • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field
  • OR equivalent experience.
• 2+ years of experience in deep learning with familiarity with Language models, transformers like BERT, GPT-2/GPT-3, Llama, OPT etc. 
• 2+ years' experience optimizing large language models, model compression, network distillation into small language models.  
• 2+ years' experience with Python. 

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 4+ years related experience with Machine Learning (ML), Natural Language Processing (NLP), Large Language Models (LLM).
  • OR Master's Degree in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 3+ year(s) related experience with Machine Learning (ML), Natural Language Processing (NLP), Large Language Models (LLM).
  • OR Doctorate in Statistics, Econometrics, Computer Science, Electrical or Computer Engineering, or related field AND 1+ years related experience with Machine Learning (ML), Natural Language Processing (NLP), Large Language Models (LLM
  • OR equivalent experience.

• Experience in model quantization & optimization techniques such as GPTQ, LORA etc .  

• Demonstrated record of publications in top-tier conferences or journals (ICLR, ACL, ICML, CVPR, ICCV, ECCV, NeurIPS, TPAMI, etc.).  

• Experience in creating APIs, SDKs and software packages for third parties.  

• Experience using dataset curation, data generation using prompting state of art LLMs, automated model evaluation.  

• Experience with model conversion and deployment frameworks like ONNX is a plus. 
• Experience with other model frameworks like Pytorch or Tensforflow etc is a plus. 
• Demonstrated ability and passion for incubating new ideas, solving problems, and building working systems.  

 

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.

 

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

Microsoft will accept applications and processes offers for these roles on an ongoing basis.

 

 

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.  We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form.

 

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

 

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