Senior ML Engineer (Digital Twin)

We’re working with a company building AI systems that interact directly with the physical world at scale — designing experiments, controlling hardware, and dramatically accelerating scientific discovery. They’re looking for a Senior Digital Twin ML Engineer to help develop high-fidelity digital twins that sit at the core of learning, simulation, and decision-making systems.

What You’ll Do

• Develop model identification pipelines, parameter fitting routines, and adaptive calibration systems for digital twins.
• Build ML-driven dynamic models, multi-scale physics approximators, and hybrid simulation frameworks.
• Maintain twin fidelity, stability, and consistency as physical systems evolve and new data is introduced.
• Collaborate with simulation, reinforcement learning, controls, and agent systems teams to integrate digital twins into closed-loop learning and decision workflows.

What We’re Looking For

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

Comp: $200,000–$300,000 base salary, depending on experience

Location: SF Based

Interested? Apply now!