Substrate is a San-Francisco–based startup developing particle-accelerator-powered X-ray lithography to manufacture cutting-edge semiconductor chips at far lower cost than existing EUV methods.
[https://app.ashbyhq.com/api/images/user-content/e51d0177-9380-4cb7-9c7b-9de4a098df50/f482ac86-3905-4e5f-9b7a-b0e7692cf436/black_logomark_1000px_720.png] 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.