{"id":57509,"url":"https://alion.io/job/substrate-research-scientist-ai","title":"Research Scientist, AI","company":{"id":18865,"name":"Substrate","domain":"substrate.com","url":"https://alion.io/company/substrate","size_band":null,"is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":75,"open_postings":6,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":null,"computed_at":"2026-10-16T05:45:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":150000,"max":275000,"currency":"USD","period":"year","gross":null,"usd_annual":275000},"salary_estimate":null,"experience_years_min":5,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"JAX","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"PyTorch","optional":false},{"name":"TensorFlow","optional":false}],"status":"live","first_seen_at":"2025-10-28T11:53:13Z","employer_posted_date":"2025-10-28","last_verified_at":"2026-10-16T20:34:54Z","board_verified":true,"closed_at":null,"days_open":353,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":352},"description":"Research Scientist, AI\nSubstrate is addressing one of the most important technological problems facing the United States. At the intersection of advanced manufacturing and cutting-edge physics, we are developing technologies that will reshape the semiconductor industry and strengthen America's technological leadership. We are a team of world-class scientists, engineers, and technical experts building technology for the United States.\nSummary\nAs a Research Scientist working with AI, you will accelerate and augment R&D workflows by applying machine learning to scientific simulations and modeling while simultaneously building internal AI capabilities across the organization. This role sits at the intersection of cutting-edge physics and artificial intelligence, and you'll work hands-on to develop AI-augmented tools that enable breakthrough research, and build the infrastructure and expertise that empowers our technical teams to leverage AI in their own work. Whether you are a physicist who has embraced machine learning or an AI expert with deep scientific domain knowledge, you will play a pivotal role in defining how we utilize AI to accelerate our own internal R&D.\nResponsibilities\nIntegrate machine learning techniques to accelerate scientific simulations, modeling, and computational workflows\n\nDevelop AI-augmented tools for materials science, device physics, or accelerator physics applications\n\nBuild internal AI infrastructure and capabilities to enable research teams across the organization\n\nTrain and mentor scientists and engineers on integrating AI/ML into their research workflows\n\nImplement surrogate models, physics-informed neural networks, or generative approaches for scientific problems\n\nDevelop data pipelines and frameworks for scientific machine learning across distributed teams\n\nCollaborate with computational physicists and experimentalists to identify high-impact AI applications\n\nSet AI best practices and establish standards for ML-augmented R&D\n\nRequired Qualifications\n5+ years professional or academic research experience in physical sciences, engineering, or related field\n\n2-3+ years hands-on experience applying machine learning to scientific or technical problems\n\nStrong programming skills in Python and ML frameworks (PyTorch, TensorFlow, JAX, or similar)\n\nDeep understanding of scientific computing, numerical methods, and computational modeling\n\nProven ability to translate scientific problems into machine learning approaches\n\nExperience building tools, infrastructure, or capabilities used by technical teams\n\nPreferred Qualifications\nPhD in Physics, Materials Science, Computer Science, Applied Mathematics, or related field\n\nPublications applying ML to scientific computing, simulation, or experimental data analysis\n\nExperience with physics-informed machine learning or scientific foundation models\n\nBackground in accelerator physics, semiconductor devices, materials modeling, or related domains\n\nTrack record of enabling technical teams through tool development or mentorship\n\nSalary Range\n$150,000-$275,000 USD\nSubstrate is an equal opportunity employer. It provides equal employment opportunity to all applicants without regard to race, color, religion, national origin, disability, medical condition, marital status, sex, gender, age, military or veteran status, or any other characteristic protected by applicable federal, state, or local laws.\nSubstrate will provide reasonable accommodations to applicants with disabilities. If you need an accommodation during the hiring process, please let your recruiter know.\n Applicants must be legally authorized to work in the United States. 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