Job description

Role Description Root Access is hiring a Simulation & Software Engineer to lead the development of scalable simulation infrastructure. You will build software that automates electrical, thermal, and electromagnetic simulations and transforms their outputs into reliable training datasets. Working alongside our Machine Learning Engineer and hardware team, you will own simulation execution, data quality, and the infrastructure needed to expand coverage across electronic designs. Responsibilities - Build and maintain automated simulation pipelines, including design parameterization, solver integration, and results extraction. - Scale simulation workloads across local and cloud compute through distributed execution, scheduling, and failure recovery. - Develop workflows for parameter sweeps and design-space exploration. - Implement checks for simulation convergence, physical validity, and dataset quality. - Track simulation configurations, data provenance, and dataset versions to ensure reproducibility. - Optimize simulation throughput, compute costs, and pipeline reliability. - Collaborate with the ML team to prioritize simulations that improve model performance. - Work with hardware engineers to validate simulation results against physical measurements. Qualifications - 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.

Requirements

Must-haves

Role Description
Build and maintain automated simulation pipelines, including design parameterization, solver integration, and results extraction.
Scale simulation workloads across local and cloud compute through distributed execution, scheduling, and failure recovery.
Develop workflows for parameter sweeps and design-space exploration.
Implement checks for simulation convergence, physical validity, and dataset quality.
Track simulation configurations, data provenance, and dataset versions to ensure reproducibility.
Optimize simulation throughput, compute costs, and pipeline reliability.
Collaborate with the ML team to prioritize simulations that improve model performance.
Work with hardware engineers to validate simulation results against physical measurements.
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.

Nice-to-haves

Preferred: experience scaling solver-generated data with automation and custom integrations.

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

machine learningmlpython

Platform: ashby
Effort: quick