{"id":3611993,"url":"https://alion.io/job/microsoft-senior-software-engineer-ai-for-science","title":"Senior Software Engineer, AI for Science","company":{"id":18,"name":"Microsoft","domain":"microsoft.com","url":"https://alion.io/company/microsoft","size_band":"5000+","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Eightfold","truth_index":{"grade":"B","score":83,"open_postings":419,"ghost_share":0.005,"stale_share":0.635,"repost_share":0.026,"time_to_fill_p50_days":29,"computed_at":"2026-11-04T06:34:25Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Cambridge, United Kingdom","Berlin, Germany","Amsterdam, Netherlands"],"countries":["GB","DE","NL"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":74700,"max":122600,"currency":"GBP","period":"year","gross":null,"usd_annual":164206},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"C++","optional":false},{"name":"Fortran","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"CUDA","optional":true},{"name":"Triton","optional":true}],"status":"live","first_seen_at":"2026-10-28T18:25:01Z","employer_posted_date":"2026-11-02","last_verified_at":"2026-11-04T09:48:57Z","board_verified":true,"closed_at":null,"days_open":6,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":6},"description":"OverviewAt Microsoft Research AI for Science we believe deep learning has the potential to transform scientific modelling and discovery crucial for solving the most pressing problems facing society, including sustainable materials and discovery of new drugs.\nFor our labs in Amsterdam (NL), London (UK), Cambridge (UK), and Berlin (DE), we seek highly motivated research software engineers to join our density functional theory (DFT) team (What is DFT?). 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.\nThe primary focus of this role will be integrating our deep learning models into high-performance DFT software frameworks, making them efficient, robust, and accessible to users. You will work on model integration, numerical algorithms, GPU acceleration, and the software infrastructure needed to bring our models into real-world scientific workflows. If you have solid software engineering expertise and enjoy bringing machine learning models into high-performance scientific software, we encourage you to apply.\nThis post will be open until the positions are filled.\nResponsibilities\nCollaborate with internal and external parties on integrating our deep learning models in high-performance DFT software frameworks, targeting both CPU and GPU-based frameworks\nPrepare and maintain open-source releases and releases for beta testers\nWrite custom efficient GPU implementations for our deep learning models \nWork cross-functionally with deep learning and quantum chemistry researchers and engineers to align model development strategies with high-performance integration into CPU and GPU-based DFT software frameworks.\nQualifications\nRequired qualifications:\nMSc in computer science, mathematics, physics, chemistry, or a related area\nProficiency in collaborative software engineering in Python and in C++ or Fortran\nExperience with maintenance of open-source libraries or commercial software packages\nUnderstanding CPU and GPU compute architecture fundamentals\nExperience with agentic software development\nAbilityto work in an interdisciplinary collaborative environment, through effective communication of technical concepts to non-experts from different technical backgrounds\nQualifications that are considered a plus, but are not strictly required:\nPhD degree in computer science, mathematics, physics, chemistry, or a related area or comparable industry experience\nExperience with CUDA/Triton programming. \nExperience with developing and optimizing numerical methods for high-performance computing platforms.\nExperience with development of high-performance DFT or quantum chemistry software\nSoftware 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.\nFind additional benefits and pay information here:\nhttps://careers.microsoft.com/v2/global/en/corporate-pay/united-kingdom-corporate-pay.html\nSoftware 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. \nFind additional benefits and pay information here:\nhttps://careers.microsoft.com/v2/global/en/corporate-pay/germany-corporate-pay.html\nSoftware 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. \nFind additional benefits and pay information here:\nhttps://careers.microsoft.com/v2/global/en/corporate-pay/netherlands-corporate-pay.html\nThis position will be open for a minimum of 5 days, with applications accepted on an ongoing basis until the position is filled.\nMicrosoft 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. 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