Principal Software Engineer, Simulation Engine

General Motors•Sunnyvale, CA

6d•$296,300 - $453,900

About The Position

The Simulation organization is solving one of the most challenging problems in autonomous driving: rigorously evaluating the performance, safety, and limitations of the autonomous driving software stack before it reaches public roads. As a Principal Software Engineer on the Simulation Engine team, you will define the technical direction for the simulation platforms that enable high-fidelity, high-performance validation of the autonomy stack and the gym environments used to train reinforcement learning models. You will operate at the intersection of autonomous driving, simulation, machine learning, infrastructure, and developer productivity, shaping capabilities that influence the broader engineering organization. This role is for a recognized technical leader who can turn ambiguous, high-impact problems into durable platform strategy and measurable engineering outcomes. You will establish architectural direction, align senior leaders across organizations, raise engineering standards, and create leverage for teams building, training, testing, and validating autonomous driving systems.

Requirements

Bachelor’s, master’s, or doctoral degree in Computer Science, Robotics, Machine Learning, or a related field, or equivalent professional experience.
12+ years of relevant software engineering experience, including significant ownership of complex, production-quality platforms or systems.
Expert programming ability in modern C++ and Python, with deep expertise in object-oriented design, software architecture, and systems engineering.
Demonstrated record of defining technical strategy and delivering transformational, cross-functional initiatives with broad organizational impact.
Experience serving as an architectural authority across multiple teams, products, or engineering organizations.
Track record of influencing senior technical and business leaders and aligning organizations around difficult tradeoffs and long-term investments.
Strong customer orientation, with experience converting developer, researcher, or validation needs into widely adopted platform capabilities.
Demonstrated ability to improve engineering quality, velocity, reliability, or operational effectiveness at organizational scale.
Exceptional written and verbal communication skills, including the ability to make complex technical topics clear to diverse audiences.
Passion for safe, fully electric, self-driving technology and its potential impact on the world.

Nice To Haves

Deep experience building, extending, or operating autonomous vehicle or robotics simulation platforms.
Experience with game engines or physics platforms such as Unity, Unreal Engine, or PhysX.
Experience designing reinforcement learning environments, training infrastructure, or simulation-based machine learning systems.

Responsibilities

Define and champion the long-term technical vision, architecture, and strategic roadmap for simulation, validation, and reinforcement learning infrastructure.
Establish architectural principles and platform strategies that enable scalable, high-fidelity, deterministic, and performant simulation across the autonomy organization.
Identify the most consequential technical opportunities and systemic risks across simulation workflows, translating them into prioritized investments and clear execution plans.
Lead the resolution of complex, cross-organizational technical problems that span autonomy software, machine learning, validation, infrastructure, data, and developer tooling.
Set direction for core simulation abstractions, APIs, execution models, scenario and sensor modeling, quality standards, and integration patterns.
Drive adoption of common platforms and engineering practices across teams, reducing fragmentation and increasing development and validation velocity.
Influence investment decisions, technical priorities, and organizational alignment through clear written proposals, architecture reviews, and executive-level communication.
Sponsor and guide high-impact initiatives from strategy and problem definition through delivery, adoption, operational maturity, and continuous improvement.
Define measurable standards for fidelity, performance, reliability, determinism, scalability, and developer experience, and use them to drive sustained improvement.
Serve as a senior technical advisor and multiplier for engineering leaders and teams, mentoring principal, staff, and senior engineers through technical direction and sponsorship.
Represent the organization’s technical perspective in broader company forums and, when appropriate, in the external autonomous driving and simulation communities.