Machine Learning Engineer

Focused is building data-driven intelligence for clean energy and fusion initiatives through an ambitious Digital Twin architecture. In this onsite role in Austin, TX, you will bridge machine learning engineering and computational physics to accelerate multiphysics simulations, integrate HPC outputs with sensor data, and improve optimization and diagnostics for laser subsystems.

What you’ll do

• Design and deploy surrogate and reduced-order models (ROMs) to replace or accelerate high-fidelity multiphysics simulations within the Digital Twin environment
• Develop physics-informed machine learning (PIML) and physics-informed neural networks (PINNs) that embed physical constraints such as Maxwell’s equations, thermodynamics, and fluid dynamics directly into model architectures
• Build and maintain ML pipelines for training, validation, uncertainty quantification (UQ), and continuous refinement against both experimental and simulation data
• Implement active learning and Bayesian optimization workflows to guide design space exploration and reduce costly simulation runs
• Integrate trained models into the broader Digital Twin framework by interfacing with HPC simulation outputs (COMSOL, ANSYS, custom solvers) and real-time sensor data
• Create anomaly detection and predictive diagnostics models to monitor system health and flag off-nominal behavior in laser subsystems
• Apply reinforcement learning and Bayesian control approaches to enable autonomous or semi-autonomous optimization of laser operating parameters
• Collaborate with Digital Twin architects, systems engineers, and optical simulation scientists to meet fidelity, latency, and uncertainty requirements
• Set up best practices for model versioning, reproducibility, testing, and documentation in a fast-moving research environment

What you bring

• Master’s or PhD in Machine Learning, Computational Physics, Applied Mathematics, Data Science, Computer Science, or a closely related field
• Proven experience building, training, and deploying ML models for complex physical systems, with strong deep learning skills in PyTorch, TensorFlow/JAX, plus probabilistic modeling and uncertainty quantification
• Expert-level Python; proficiency in C++ or Fortran is a plus; experience with HPC environments including batch schedulers and MPI/OpenMP
• Fluency working with PDE-based simulation outputs, time-series sensor data, and high-dimensional parameter spaces common in multiphysics settings
• Hands-on experience with Gaussian processes, neural network surrogates, reduced-order models, or comparable metamodeling techniques
• Experience building robust ML pipelines for scientific data, including preprocessing, feature engineering, validation, and deployment
• Ability to clearly communicate model behavior, confidence intervals, and limitations to physicists, engineers, and non-ML specialists
• Strong cross-functional collaboration skills in an interdisciplinary environment spanning physics, engineering, and software

Technologies you may work with

PyTorch, TensorFlow, JAX, C++, Fortran, COMSOL, ANSYS, MPI, OpenMP, Gaussian processes, NVIDIA Omniverse, Siemens Xcelerator, ANSYS Twin Builder, DeepONet, FNO, MLflow, Weights & Biases, DVC

Nice to have

• Experience with physics-informed neural networks (PINNs) or neural operators (DeepONet, FNO) on physical systems
• Background in laser physics, plasma physics, high-energy-density science, or related domains
• Experience with Digital Twin platforms and live integration of ML models (NVIDIA Omniverse, Siemens Xcelerator, ANSYS Twin Builder)
• Familiarity with multidisciplinary design optimization workflows including Design of Experiments (DoE), sensitivity analysis, and uncertainty propagation
• Experience applying reinforcement learning to physical system control or optimization
• Familiarity with Monte Carlo methods and statistical uncertainty quantification frameworks
• Interest in scientific computing MLOps tooling including MLflow, Weights & Biases, and DVC
• Interest in fusion energy, advanced laser systems, or high-energy-density physics

Benefits and culture

• Competitive salary and company ownership through stock options
• Medical, Dental, Vision with multiple plans active starting on the 1st Day of employment
• Unlimited PTO
• Healthy snacks and drinks in the office
• 401k match up to 4% on top of the employee contribution
• State-of-the-art Windows or Apple laptops plus additional equipment (keyboard, mouse, and headset)
• Regular events to support team bonding and collaboration

What Focused offers

• Innovative technology and mission: work on groundbreaking research in clean energy and scientific discovery
• Career development: join an early, growing company investing in people and new technology
• Collaborative culture: an international environment with top-tier scientists, engineers, and professionals
• Ownership: take ownership from day one and shape decisions, solutions, and the company’s future