Applied Scientist - Munich, Deutschland - Microsoft

Microsoft

Geprüftes Unternehmen

Munich, Deutschland

vor 3 Wochen

Geschrieben von:

Lena Wagner

beBee Recruiter

Beschreibung

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 software 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.

Requirements:

Must be a strong machine learning researcher.
Must be passionate about incubating new ideas, solving problems, and building working systems.
Must be selfmotivated, 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.

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 realtime system involving multiple components.
Assist in identifying and addressing issues in ML frameworks and associated hardware.
Mentor junior engineers and contribute to team knowledgesharing sessions.

Qualifications:

Must have experience in the following:

Minimum 3 years of experience in deep learning with familiarity with Language models, transformers like BERT, GPT-3, Llama
Experience optimizing large language models, model compression, network distillation into small language models.
Experience with Parameter-Efficient Fine-Tuning methods for foundational models.
Experience on building multilingual language models.
Strong demonstrable experience with natural language processing.
Minimum 3 years of Python experience

Additional or Preferred Qualifications:

Experience with other model frameworks like Pytorch or Tensforflow etc is a plus.
Experience with distributed training libraries like DeepSpeed is a plus.
Experience in model quantization & optimization techniques such as GPTQ, LORA etc.
Record of publications in toptier conferences or journals (ICLR, ACL, ICML, CVPR, ICCV, ECCV, NeurIPS, TPAMI, etc.)
Experience in creating APIs, SDKs and software packages for third parties.