Strong software engineering skills in Python, with a focus on building reliable automated systems.
Experience with physics-based simulation tools and numerical solvers.
Familiarity with parallel computing and cloud or HPC infrastructure.
Knowledge of data pipelines, structured storage, and reproducible workflows.
Understanding of numerical methods in circuit simulation, electromagnetics, or thermal analysis.
Ability to diagnose solver failures and differentiate software issues from modeling problems.
Degree in engineering, physics, applied mathematics, computer science, or equivalent experience.
Responsibilities
Build and maintain automated simulation pipelines, including design parameterization and results extraction.
Scale simulation workloads across local and cloud compute through distributed execution and scheduling.
Develop workflows for parameter sweeps and design-space exploration.
Implement checks for simulation convergence and dataset quality.
Track simulation configurations and data provenance for reproducibility.
Optimize simulation throughput and pipeline reliability.
Collaborate with the ML team to prioritize simulations that enhance model performance.
Benefits
Opportunity to lead the development of scalable simulation infrastructure.
Collaborative work environment with cross-functional teams.
Engagement in cutting-edge technology and simulation methodologies.
Potential for professional growth in a rapidly evolving field.
Full 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.
