Systems Engineer - Simulation Correctness (Senior)

Vinci4d•Palo Alto, CA

4d•$190,000 - $250,000

About The Position

Vinci is seeking a Senior Systems Engineer specializing in Simulation Correctness to join their team. The company is developing operator intelligence infrastructure for modern hardware programs, leveraging a foundational model trained on PetaBytes of structured physics data that performs billion-voxel inference in production for Tier-1 semiconductor and hardware customers. Vinci aims to significantly increase simulation throughput, expand simulation capabilities, and support global, multi-entity deployment. The role involves integrating Machine Learning with classic numerical approaches to reduce simulation complexity, making them easier to set up, run, and evaluate quickly. The Systems Engineer will be responsible for the empirical validation of simulation systems, evaluating cutting-edge solutions from Machine Learning and Solver teams, and building a runtime evaluation mechanism with data-driven arguments. This role requires collaboration with software engineers to implement designs and demonstrate validity, working at the intersection of Physicists, AI researchers, Software Engineers, and Computational Geometry experts.

Requirements

Prior experience using or building physics simulators (FEM, FEA, Molecular Dynamics, FDTD).
Experience as a systems engineer in a production environment.
Experience working with Scientists and Engineers in a collaborative setting.
Basic understanding of solver mechanisms (Numerical Optimization, Convergence Criteria, Dampening approaches).
Working knowledge of ML basics (back prop, loss functions, generators, embeddings, transformer models).
Understanding of statistics and data science methods (Confidence intervals, uncertainty quantification, Bayes method).
Software engineering fundamentals.
Understanding of CI, regression testing, and validation discipline.
Excellent communication and documentation skills.
Comfortable running thousands of simulations and finding a needle in the haystack failure.
Capable of defining an architecture with sufficient detail an Engineer could implement it with few open questions.

Nice To Haves

Worked as a Systems Engineer for a production Software Solution in Robotics, Chip Manufacturing, or Aerospace.
Leveraged simulation for design or data generation purposes.
Experience delivering solutions when needed.
Worked on validation solutions for a production ML system.

Responsibilities

Guaranteed (empirical) validation of simulation systems.
Use and evaluate cutting-edge solutions developed by Machine Learning and Solver teams.
Build a runtime evaluation mechanism to ensure customers receive the highest value results.
Develop a compelling data-driven argument for the evaluation mechanism.
Work with software engineers to implement designs and demonstrate validity.
Run thousands of simulations and identify failure points.