Acceler8 Talent
Senior Machine Learning Engineer (San Francisco)
Acceler8 Talent, San Francisco, California, United States, 94199
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!
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!