Physics-Infused ML Engineer for Digital Twins

Focused; Austin (TX); On-site; USD 120,000 - 190,000; Full time

Benefits offered by this job

Stock options

Medical, Dental, Vision plans

Unlimited PTO

401k match

Equipment provided

Job summary

Focused Energy in Austin is advancing clean energy through ML-powered digital twin technology for laser fusion. You will embed data-driven intelligence into multiphysics simulations, accelerating design cycles and enabling real-time decision support across laser, targetry, and fusion programs.

You will design, build, and deploy ML models, collaborate with optical engineers and physicists, and deploy robust ML pipelines in a fast-moving research environment focused on rigor and reproducibility.

Qualifications

• Must have advanced degree in ML, computational physics, or related field.
• Proven experience building, training, deploying ML for complex physical systems.
• Expert-level Python; C++/Fortran a plus; HPC experience.
• Fluency with PDEs, time-series data, and high-dimensional parameter spaces.
• Experience in ML pipelines, validation, and deployment.

Responsibilities

• Design, build, and deploy ML models for multiphysics simulations.
• Develop surrogate and reduced-order models to accelerate high-fidelity simulations.
• Create physics-informed ML models and PINNs.
• Build ML pipelines for training, validation, and uncertainty quantification.
• Implement active learning and Bayesian optimization for design space exploration.
• Integrate ML models into Digital Twin and HPC environments.
• Develop anomaly detection and predictive diagnostics for laser subsystems.
• Collaborate with engineers and scientists to meet fidelity and latency targets.

Skills

ML engineering

Python

C++

HPC

PDEs

Uncertainty quantification

DL frameworks

Communication

Education

Master's or PhD in ML/Computational Physics

Tools

PyTorch

TensorFlow/JAX

COMSOL/ANSYS

MPI/OpenMP

Job description

Focused Energy in Austin is advancing clean energy through ML-powered digital twin technology for laser fusion. You will embed data-driven intelligence into multiphysics simulations, accelerating design cycles and enabling real-time decision support across laser, targetry, and fusion programs.

You will design, build, and deploy ML models, collaborate with optical engineers and physicists, and deploy robust ML pipelines in a fast-moving research environment focused on rigor and reproducibility.