Research Scientist, AI
Substrate
San Francisco, CA · Posted October 28, 2025
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Where San Francisco, CA ranks
Where San Francisco, CA placed in our monthly rankings, month by month. Each month stays online at its own address.
November 2026
- #1Best cities for security jobs316 openings · of 20
- #1Best cities for technology jobs7,178 openings · of 100
- #1Best cities for financial services pay after cost of living$173k · of 33
- #1Best cities for entry-level jobs that want AI skills35% · of 100
- #1Best cities for entry-level jobs that want AI skills in the West Coast35% · of 54
- #1Cities with the most jobs that do not need a four-year degree in the West Coast902 jobs · of 47
Rankings about data & analytics jobs
- Best cities for data and analytics jobs #1 New York (1,713 openings)
- Best cities for data and analytics pay after cost of living #1 Foster ($232k)
- Most requested AI skills in data and analytics jobs #1 Machine learning engineering (17.1%)
- AI tools named most often in data and analytics jobs #1 Databricks (7.6%)
- Employers with the most data and analytics jobs #1 Amazon (711 roles)
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Pay compared with the market
This listing does not state pay. Across 62 open research scientist listings that state pay, the middle half runs $195,500 to $300,000 and the median is $239,500.
Listed pay is what employers advertise, not what people are paid.
How AI is used in this kind of work
AI use among medical scientists, except epidemiologists is little observed so far. Measured exposure for medical scientists, except epidemiologists: 4% (little observed).
Share of this job’s tasks that AI is already used for at work, from real usage. It is not a forecast of job loss, and a low number means no use seen yet. Source: Anthropic Economic Index.
Skills this job asks for
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About the job
Research Scientist, AI
Substrate 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.
Summary
As 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.
Responsibilities
• Integrate machine learning techniques to accelerate scientific simulations, modeling, and computational workflows
• Develop AI-augmented tools for materials science, device physics, or accelerator physics applications
• Build internal AI infrastructure and capabilities to enable research teams across the organization
• Train and mentor scientists and engineers on integrating AI/ML into their research workflows
• Implement surrogate models, physics-informed neural networks, or generative approaches for scientific problems
• Develop data pipelines and frameworks for scientific machine learning across distributed teams
• Collaborate with computational physicists and experimentalists to identify high-impact AI applications
• Set AI best practices and establish standards for ML-augmented R&D
Required Qualifications
• 5+ years professional or academic research experience in physical sciences, engineering, or related field
• 2-3+ years hands-on experience applying machine learning to scientific or technical problems
• Strong programming skills in Python and ML frameworks (PyTorch, TensorFlow, JAX, or similar)
• Deep understanding of scientific computing, numerical methods, and computational modeling
• Proven ability to translate scientific problems into machine learning approaches
• Experience building tools, infrastructure, or capabilities used by technical teams
Preferred Qualifications
• PhD in Physics, Materials Science, Computer Science, Applied Mathematics, or related field
• Publications applying ML to scientific computing, simulation, or experimental data analysis
• Experience with physics-informed machine learning or scientific foundation models
• Background in accelerator physics, semiconductor devices, materials modeling, or related domains
• Track record of enabling technical teams through tool development or mentorship
Salary Range
$150,000-$275,000 USD
Substrate 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.
Substrate will provide reasonable accommodations to applicants with disabilities. If you need an accommodation during the hiring process, please let your recruiter know.
Applicants must be legally authorized to work in the United States. This position is not eligible for visa sponsorship.