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Senior Research Software Development Engineer, MSR AI for Science at Microsoft
Berlin, North Holland, Germany -
Full Time

Start Date

Immediate

Expiry Date

25 Feb, 26

Salary

0.0

Posted On

27 Nov, 25

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

No

Skills

Machine Learning, Scientific Research, Data Processing, Model Building, Distributed Systems, Cloud Computing, HPC Environment, Tensor Accelerators, GPUs, Analytical Skills, Problem-Solving, Communication Skills, Open Source Frameworks, Materials Science, Density Functional Theory

Industry

Software Development

Description
Architect, design, and implement scalable and robust solutions for machine learning and scientific research involving large volumes of heterogeneous data. Build and optimize distributed data processing and model building pipelines. Develop and maintain tools and technologies for building, training, optimizing, scaling machine learning solutions. Collaborate with cross-functional teams, including scientists, researchers, and software engineers. Document and share best practices across the organization. Maintain the highest standards in code quality and software design. Required: Master's degree or equivalent work experience in Computer Science, Physics, Engineering, Chemistry, Mathematics or a related field. Strong familiarity with Linux and the open-source ecosystem. Proficient working with large datasets in a cloud or HPC environment. Proficient in building and optimizing distributed systems and large-data applications, including those using tensor accelerators or GPUs. Strong analytical, problem-solving, and communication skills. Passionate about pushing the boundaries of science. Prior experience developing high-performance scientific software is not required, but preferred. Experience with open source machine learning frameworks (e.g., PyTorch, ggml, llama.cpp, vllm) is a plus. Experience with Materials Science (in particular Density Functional theory) is a plus.
Responsibilities
Architect, design, and implement scalable solutions for machine learning and scientific research. Collaborate with cross-functional teams and maintain high standards in code quality.