Machine Learning Engineer (m/f/d)

Must-Haves

• 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; strong command of deep learning (PyTorch, TensorFlow/JAX), probabilistic models, and uncertainty quantification
• Expert-level Python; proficiency in C++ or Fortran a plus; experience with HPC environments (batch schedulers, MPI/OpenMP parallelization)
• Fluency working with PDE-based simulation outputs, time-series sensor data, and high-dimensional parameter spaces typical of multiphysics environments
• Hands-on experience with Gaussian processes, neural network surrogates, reduced-order models, or equivalent metamodeling techniques
• Experience building robust ML pipelines for scientific data — including preprocessing, feature engineering, model validation, and deployment
• Ability to communicate model behavior, confidence intervals, and limitations clearly to physicists, engineers, and non-ML specialists
• Strong cross-functional team skills; comfort working in an interdisciplinary environment spanning physics, engineering, and software

Nice-to-Haves

• Experience with physics-informed neural networks (PINNs) or neural operators (DeepONet, FNO) applied to physical systems
• Background in laser physics, plasma physics, high-energy-density science, or related complex physics domains
• Experience with digital twin platforms and live integration of ML models with simulation environments (e.g., NVIDIA Omniverse, Siemens Xcelerator, ANSYS Twin Builder)
• Familiarity with multidisciplinary design optimization (MDO) 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
• Experience with MLOps tooling (MLflow, Weights & Biases, DVC) in a scientific computing context
• Interest in fusion energy, advanced laser systems, or high-energy-density physics

Focused Energy is an equal opportunity employer committed to creating an inclusive environment. Qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender perception or identity, national origin, age, marital status, protected veteran status, or disability status.

Pursuant to the San Francisco Fair Chance Ordinance, Focused Energy will consider for employment qualified applicants with arrest and conviction records.

Compensation offered will be determined by factors such as location, level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, benefits.

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