PhysicsX
Machine Learning Engineer
$150K–$190K
San Francisco, CA +1 · Full-time · Posted Jun 2, 2026
- Location
- San Francisco, CA
San Francisco, California, United States - Experience
- At least 2 years of industry experience post-Masters or PhD in a commercial, non-research environment; also states 2+ years’ experience in a data-driven role.
- Education
- Background in Physics, Engineering, or equivalent.
About the job
Build and deliver reliable, scalable machine-learning systems that turn engineering and physics challenges into practical customer-facing tools and products.
What you'll do
- Develop, test, and deploy ML data pipelines; explore and manipulate 3D point-cloud and mesh data.
- Own technical workstreams and create cloud or on-premise analytics environments with engineering, data science, and customer teams.
- Translate R&D and project results into reusable libraries, tooling, and products, while improving engineering practices.
What they ask for
- Experience applying machine-learning methods, including 3D graph or point-cloud deep learning, to real-world engineering applications.
- Track record of scoping and delivering projects in a customer-facing role.
- 2+ years’ experience in a data-driven role, with exposure to software engineering concepts and best practices.
- Background in Physics, Engineering, or equivalent.
Nice to have
- Industrial ML, computational statistics, or modelling experience, such as supply-chain optimisation or manufacturing processes.
- Experience with distributed computing, cloud platforms, high-performance computing, containerization, and orchestration.
Pay
$150,000 - $190,000 USD base salary
Tools
Python, TensorFlow, MLFlow, Spark, Dask, AWS, Azure, GCP, Docker
AI focus
Apply machine learning, including 3D graph and point-cloud deep learning, to industrial engineering and physics challenges; deploy AI models as practical customer solutions.
Model-written summary · the original posting is authoritative