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Senior Research Engineer Machine Learning, AI for Science

Microsoft Corporation

DEJob£75–123K/yrPosted 1 day agoStill listed today

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At a glance

Compensation
£75–123K/yr
Location
DE
Work Authorization
Not specified

Olive lists jobs from US employers, including remote roles you can work from the United States.

Requirements

Credentials this posting asks for.

Master's degree

Job overview

The team develops deep learning-powered density functional theory methods for accurate, scalable predictions of molecular and materials electronic structure. This role focuses on building and maintaining infrastructure for large-scale model training, evaluation, and benchmarking, including scientific data pipelines, distributed training, experimentation, and agentic workflows. The engineer works with machine learning researchers, engineers, and natural scientists.

Skills & qualifications

RequiredNice to have

Skills

Machine LearningPython (Programming Language)Deep LearningData PipelineDistributed ComputingSoftware EngineeringCollaborationCloud Platform SystemHigh Performance ComputingCollaborative Software EngineeringMachine Learning FrameworksPyTorchJAXML SystemsAgentic Software DevelopmentDistributed SystemsLarge-Data ApplicationsTensor AcceleratorsGPUsTechnical CommunicationCloud PlatformsHPCHigh-Performance Scientific SoftwareAgentic FrameworksOrchestration SystemsAI Agent Infrastructure

Qualifications

Completed MSc in Related FieldPhD in Related Field or Comparable Industry Experience

Full job description

Overview The mission of the team is to enable highly accurate and scalable predictions of the electronic structure of molecules and materials using deep learning-powered DFT. Accurate predictions of electronic structure are essential for predictive modeling across chemistry and materials science. Learn more about our work on accurate and scalable DFT in our blog and on our project website. The primary focus of this role will be developing and maintaining efficient, reliable end-to-end infrastructure for large-scale model training, evaluation, and benchmarking, including large-scale data pipelines for heterogeneous scientific data, distributed training, experimentation, and agentic workflows. If you have solid machine learning engineering expertise and enjoy building scalable infrastructure that enables cutting-edge machine learning research, we encourage you to apply. This post will be open until the positions are filled.

Responsibilities

  • Develop and maintain efficient, reliable, and scalable infrastructure for large-scale machine learning training, evaluation, and benchmarking.
  • Architect, design, and implement large-scale data pipelines for heterogeneous scientific data, supporting efficient model training, experimentation, evaluation, and benchmarking.
  • Build and optimize distributed data processing, model training, evaluation, and benchmarking pipelines.
  • Develop software and agentic workflows to automate and improve model development, training, evaluation, and benchmarking.
  • Continuous monitoring and improvement of the stability of data, training, evaluation and benchmarking workflows
  • Work cross-functionally with machine learning researchers, engineers, and researchers from the natural sciences.
  • Maintain high standards in code quality and software design.
  • Document and share practices across the organization.

Qualifications Required qualifications:

  • Completed MSc in computer science, machine learning, AI or a related area
  • Proficiency in collaborative software engineering in Python
  • In-depth understanding of machine learning frameworks such as PyTorch and/or Jax
  • Experience in designing, developing and deploying ML systems
  • Experience with agentic software development
  • Experience building and optimizing distributed systems and large-data applications, including those using tensor accelerators or GPUs.
  • Ability to work in an interdisciplinary collaborative environment, through effective communication of technical concepts to non-experts from different technical backgrounds

Qualifications that are considered a plus, but are not strictly required:

  • PhD degree in computer science, machine learning, AI or a related field, or comparable industry experience in working with machine learning and large datasets.
  • Experience working with major cloud platforms and/or HPC
  • Experience developing high-performance scientific software.
  • Experience designing or developing agentic frameworks, orchestration systems, or infrastructure for building and running AI agents.

Software Engineering IC4 - The typical base pay range for this role across United Kingdom is £ 74,700.00 - £ 122,600.00 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/united-kingdom-corporate-pay.html

Software Engineering 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

Software Engineering 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

Software Engineering IC4 - The typical base pay range for this role across United Kingdom is £ 74,700.00 - £ 122,600.00 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/united-kingdom-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.

How this job compares

Set against the 1,192 open Research Engineer jobs on Olive Jobs, counted November 5, 2026.

Pay
  • This posting£75–123K/yr
  • US median$147–257K/yr867 salary ranges

This range's midpoint, $125K, is 41% below the US median midpoint ($213K) — in the lowest quarter of Research Engineer salary ranges across the US.

Openings
Olive Jobs lists 1,192 open Research Engineer jobs across the US. 6% of them nationwide are listed as remote or flexible.
Hiring the most across the US
Experience
Research Engineer postings that state a minimum ask for 3 years of experience at the median; the middle half ask for 2 to 5 years (672 postings).
Education
This posting asks for a master's degree; 157 of the 1,192 open Research Engineer jobs (13%) ask for a master's degree or higher.

Counted across the open, public US postings on Olive Jobs on November 5, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.

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