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Root Access is seeking a Simulation & Software Engineer to lead the development of scalable simulation infrastructure that automates electrical, thermal, and electromagnetic simulations and transforms their outputs into reliable training datasets for machine learning models.
You will own the full lifecycle of simulation execution, from design parameterization and solver integration to results extraction and data quality assurance. Your responsibilities include building and maintaining automated simulation pipelines, scaling simulation workloads across local and cloud compute environments through distributed execution and scheduling, and developing workflows for parameter sweeps and design-space exploration. You will implement rigorous checks for simulation convergence, physical validity, and dataset quality, while tracking simulation configurations, data provenance, and dataset versions to ensure reproducibility and traceability.
You will optimize simulation throughput, compute costs, and pipeline reliability, collaborating closely with the Machine Learning Engineer to prioritize simulations that improve model performance and with hardware engineers to validate simulation results against physical measurements. This role requires diagnosing solver failures, distinguishing software issues from modeling problems, and continuously improving the infrastructure to expand coverage across electronic designs.
REQUIREMENTS:
- Strong software engineering skills in Python with experience building reliable automated systems
- Experience with physics-based simulation tools, numerical solvers, or scientific computing
- Experience with parallel computing, workload orchestration, and cloud or HPC infrastructure
- Familiarity with data pipelines, structured storage, versioning, and reproducible workflows
- Understanding of numerical methods and at least one relevant domain: circuit simulation, electromagnetics, or thermal analysis
- Ability to diagnose solver failures and distinguish software issues from modeling problems
- Degree in engineering, physics, applied mathematics, computer science, or equivalent experience
- Preferred: experience scaling solver-generated data with automation and custom integrations
