Senior Machine Learning Engineer

Senior Digital Twin ML Engineer - San Francisco, CA 

A company building AI systems that can interact with the physical world at scale - designing experiments, controlling hardware, and accelerating scientific discovery from days to reality are looking for a Senior Digital Twin ML Engineer to join their team.

What Will I Be Doing: 

• Develop model-identification pipelines, parameter fitting routines, and adaptive calibration systems for digital twins
• Build ML-based dynamic models, multi-scale physics approximators, and hybrid simulation frameworks
• Ensure twin fidelity, stability, and cross-version consistency as real systems evolve and new data arrives
• Collaborate with simulation, RL, controls, and agent systems teams to integrate digital twins into learning and decision-making workflows

What We're Looking For:

• Strong experience building or calibrating digital twins, dynamic models, or data-driven physics models
• Familiarity with system identification, time-series modeling, physical parameter estimation, and stability/fidelity considerations
• Ability to blend physics intuition, machine learning, and experimental data into robust predictive models
• Comfortable working across ML, simulation tools, and physical hardware interfaces in a fast-moving environment

What's In It For Me:

• Salary of $200,000 - $300,000 dependent on experience
• Greenfield work. Build something that doesn't exist, at the frontier of physical AI and automated hardware design
• Real impact. Control actual physical systems contributing to breakthroughs in cancer detection, materials science, and more
• Join a company backed by significant venture funding and a $42M government research programme

Apply now for immediate consideration!