Systems Engineer - Simulation Correctness

Vinci • Palo Alto, CA

2d

About The Position

Vinci is building operator intelligence infrastructure for hardware programs, combining machine learning with classic numerical approaches to make physics simulations easier to set up, run, and evaluate while improving speed and accuracy. The Systems Engineer will focus on the empirical validation of simulation systems, evaluating solutions developed by the Machine Learning and Solver teams and helping ensure customers receive high-value results.

The role involves designing a runtime evaluation mechanism and developing a data-driven case for it, then partnering with software engineers to implement the design and demonstrate its validity. The engineer will work across teams of physicists, AI researchers, software engineers, and computational geometry experts, bringing systems expertise to complex technical work. This is an opportunity to be Vinci’s first Systems Engineer and build a practice and team around simulation validation as the company expands its solution into transient modeling and broader industrial deployment.

Requirements

• Prior experience using or building physics simulators, such as FEM, FEA, Molecular Dynamics, or FDTD.
• Experience as a systems engineer in a production environment, working collaboratively with scientists and engineers.
• Basic understanding of solver mechanisms, including numerical optimization, convergence criteria, and dampening approaches.
• Working knowledge of machine learning basics, including backpropagation, loss functions, generators, embeddings, and transformer models.
• Understanding of statistics and data science methods, including confidence intervals, uncertainty quantification, and Bayesian methods.
• Software engineering fundamentals.
• Understanding of CI, regression testing, and validation discipline.
• Excellent communication and documentation skills.
• Comfort running thousands of simulations and finding rare failures.
• Ability to define an architecture in sufficient detail for an engineer to implement with few open questions.

Nice To Haves

• Systems engineering experience for a production software solution in robotics, chip manufacturing, or aerospace.
• Experience leveraging simulation for design or data generation.
• Experience delivering solutions when needed.
• Experience working on validation solutions for a production ML system.

Responsibilities

• Evaluate cutting-edge solutions developed by the Machine Learning and Solver teams.
• Design a runtime evaluation mechanism for empirically validating simulation systems.
• Develop a compelling, data-driven argument for the evaluation mechanism.
• Work with software engineers to implement the design and demonstrate its validity.
• Collaborate across teams of physicists, AI researchers, software engineers, and computational geometry experts.
• Run large numbers of simulations and identify hard-to-find failures.
• Define implementation-ready architectures with sufficient detail and few open questions.
• Help establish and build Vinci’s systems engineering practice and team.

What This Job Offers

• Job Type: Full-time
• Education Level: No Education Listed