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Project Administrator
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Lead Principal Scientist
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Principal Applied Scientist - Reading, United Kingdom - Microsoft
Description
Overview
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 dedicated applied science group 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 a machine learning system: machine learning models, finetuning, data pipeline, camera optics, sensors, responsible AI and of course, developing and implementing the algorithms that make magic happen
The team is growing, and we have an exciting opportunity for talented research scientists and engineers 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 offers a competitive base salary plus bonus, excellent benefits package and stock.
Qualifications
Qualifications
• A Ph.D. in Computer Science, Math, Physics, Statistics, or related areas or Candidates with master's degree with 5+ relevant post-PhD industry experience
Must have experience in the following:
• Minimum 3 years of experience in deep learning with familiarity with LLMs like BERT, GPT-3, Llama or VLMs like Vision Transformer, CLIP, Florence
• Experience training foundation models, data collection and model distillation into smaller models.
• Experience with Parameter-Efficient Fine-Tuning methods for foundational models
• Strong demonstrable experience with multimodal foundation models
• Strong programming skills to operationalize research ideas (Python and/or C++) or a record of publishing at top-tier conferences or journals (ICLR, ACL, ICML, CVPR, ICCV, ECCV, NeurIPS, TPAMI, etc.)
• Experience with ML frameworks like Pytorch or Tensorflow
• Experience with ML inference frameworks such as ONNX Runtime or CoreML
Additional or Preferred Qualifications:
• Experience with distributed training libraries like DeepSpeed.
• Awareness or desire to learn about model compression and quantization techniques
• Experience in creating APIs, SDKs and software packages for third parties.
• Experience running large data collection exercises.
Responsibilities
Requirements
• Must be a strong machine learning researcher/engineer.
• Must be passionate about incubating new ideas, solving problems, and building working systems.
• Must be self-motivated, proven collaborators, good communicators, attentive to details, and keen to learn.
• Practical experience working in a highly performant team in an academic or industrial research environment.
• Must be comfortable adapting to the fast-paced changes in generative AI technology landscape and have a growth mindset.
Responsibilities
• Train, adapt or fine tune models destined 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.
