Senior Research Software Development Engineer, MSR AI for Science

Reposted Yesterday
Be an Early Applicant
2 Locations
Remote
79K-153K Annually
Senior level
Software • Quantum Computing • Metaverse • Infrastructure as a Service (IaaS)
The Role
Architect and implement scalable, robust systems for ML-driven scientific research. Build and optimize distributed data-processing and model-training pipelines on cloud or HPC with GPUs/tensor accelerators. Develop tools to train, optimize, and scale ML solutions, collaborate with scientists and engineers, document best practices, and maintain high code quality.
Summary Generated by Built In
Overview

We are on the cusp of a new frontier in which machine learning and artificial intelligence are transforming scientific discovery. We seek to drive major advances in sciences with machine learning, with a focus on ‘fifth paradigm’ scenarios. Through these advances, we aim to empower real-world impact on some of the most pressing problems facing society including climate change, green energy, sustainable materials, and the discovery of new drugs. 


AI for Science is a new global team in Microsoft Research focusing on the opportunity to transform scientific modelling and discovery through large-scale deep learning.  We aim to advance this frontier and to drive real-world impact at a global scale. The AI for Science team encompasses multiple disciplines across machine learning, engineering, and the natural sciences and spans several sites in Europe. 

The field of machine learning has evolved significantly in recent years, with many of the most impactful contributions coming from larger teams of people collaborating closely on well-defined and challenging goals.  Furthermore, AI for Science in particular requires a combination of machine learning, engineering, and natural sciences, which again emphasises the importance of collaboration and teamwork. 

We are seeking a highly motivated and experienced Senior RSDE with expertise in software engineering and distributed systems. The ideal candidate will have a deep understanding of distributed computing and be proficient in the design, planning, and implementation of tools and technology to support AI-driven scientific research.

To Apply: If you are excited about making a meaningful impact in AI-driven scientific research and possess the skills and experience outlined above, we encourage you to submit your resume. We look forward to reviewing your application!

#Research #AI for Science


Responsibilities
  • 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.

Qualifications

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.


Research Sciences IC4 - The typical base pay range for this role across Germany is € 90,100.00 - € 152,500.00 per year. Certain roles may be eligible for benefits and other compensation.

Find additional benefits and pay information here:
https://careers.microsoft.com/v2/global/en/corporate-pay/germany-corporate-pay.html


Research Sciences IC4 - The typical base pay range for this role across Netherlands is € 78,800.00 - € 133,300.00 per year. Certain roles may be eligible for benefits and other compensation.

Find additional benefits and pay information here:
https://careers.microsoft.com/v2/global/en/corporate-pay/netherlands-corporate-pay.html


This position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.



Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, citizenship, color, family or medical care leave, gender identity or expression, genetic information, immigration status, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran or military status, race, ethnicity, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable local laws, regulations and ordinances. If you need assistance with religious accommodations and/or a reasonable accommodation due to a disability during the application process, read more about requesting accommodations.

Skills Required

  • Master's degree or equivalent in Computer Science, Physics, Engineering, Chemistry, Mathematics or 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.
  • Experience with open source machine learning frameworks (e.g., PyTorch, ggml, llama.cpp, vllm).
  • Experience with Materials Science (in particular Density Functional Theory).

Microsoft Compensation & Benefits Highlights

The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about Microsoft and has not been reviewed or approved by Microsoft.

  • Fair & Transparent Compensation Pay is presented as broadly competitive overall, with clear role/level/location variation and an emphasis on using posted ranges and band information for apples-to-apples comparisons.
  • Retirement Support Retirement benefits are described as a standout, highlighted by a strong 401(k) match structure and immediate vesting, plus additional plan features for tax-advantaged saving.
  • Parental & Family Support Family-oriented benefits are portrayed as a meaningful strength, with substantial paid parental leave and added supports like back-up care and adoption/surrogacy assistance.

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