Job description

Our Simulation team builds the tools that engineers across the company rely on to validate autonomous vehicle safety and performance - including 3D scenario authoring tools, generative models for realistic traffic and scenario generation, and agentic tooling that automates manual simulation workflows. The team combines traditional software engineering with machine learning engineers, and the simulation coverage they deliver directly determines how many miles, scenarios, and edge cases we can validate before each autonomy release. We're looking for an Engineering Manager to lead a team of software and ML engineers building the scenario authoring tools, generative models, and agentic tooling that engineering relies on broadly to validate autonomous vehicle safety and performance. You'll own the team's technical direction - including its ongoing shift toward generative AI - while growing and developing the team, and you'll partner cross-functionally to scale our generative scenario creation capabilities as a company-wide capability with executive visibility. In this role, you will: Manage and grow a mixed team of software and machine learning engineers building simulation tools that are used broadly across engineering to validate autonomous vehicle safety and performance. Set and drive the team's technical direction, investing in agentic tooling to automate manual simulation workflows and deploying in-house generative models for exploratory vehicle testing. Lead high-visibility, cross-functional initiatives to scale the company's generative scenario creation capabilities, partnering with stakeholders across engineering and earning executive sponsorship. Own delivery of simulation tooling and services, including scenario authoring tools (e.g., 3D visual editors) used broadly across engineering teams. Ensure simulation tooling keeps pace with new Operational Design Domain (ODD) capabilities and upcoming autonomy milestones. Recruit, mentor, and develop engineers across both software and ML disciplines, including hiring ML engineers; build a strong team culture and clear growth paths. Partner with product, safety, autonomy, and validation stakeholders to prioritize the roadmap, translate business needs into technical execution, and deliver against autonomy milestones. Qualifications: 7+ years of software engineering experience, with demonstrated technical depth in simulation, developer tools, infrastructure, or a related domain. 2+ years directly managing software and/or ML engineering teams, including hiring, mentoring, and performance management. Experience partnering cross-functionally with leaders and stakeholders across engineering to prioritize and deliver a shared roadmap. Strong understanding of simulation, testing, or validation systems for complex, safety-critical software. Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience. Bonus Qualifications: Experience managing teams that combine traditional software engineering with applied ML or generative AI. Familiarity with generative models applied to simulation or testing (e.g., traffic-infilling, scenario creation, synthetic data). Experience building or scaling tools used broadly across a large engineering organization, such as visual editors and agentic authoring tools. Background in autonomous vehicles, robotics, or another safety-critical, sensor-driven domain. Track record of leading high-visibility initiatives with executive stakeholders.

Requirements

Must-haves

Manage and grow a mixed team of software and machine learning engineers building simulation tools that are used broadly across engineering to validate autonomous vehicle safety and performance.
Set and drive the team's technical direction, investing in agentic tooling to automate manual simulation workflows and deploying in-house generative models for exploratory vehicle testing.
Lead high-visibility, cross-functional initiatives to scale the company's generative scenario creation capabilities, partnering with stakeholders across engineering and earning executive sponsorship.
Own delivery of simulation tooling and services, including scenario authoring tools (e.g., 3D visual editors) used broadly across engineering teams.
Ensure simulation tooling keeps pace with new Operational Design Domain (ODD) capabilities and upcoming autonomy milestones.
Recruit, mentor, and develop engineers across both software and ML disciplines, including hiring ML engineers; build a strong team culture and clear growth paths.
Partner with product, safety, autonomy, and validation stakeholders to prioritize the roadmap, translate business needs into technical execution, and deliver against autonomy milestones.
7+ years of software engineering experience, with demonstrated technical depth in simulation, developer tools, infrastructure, or a related domain.
2+ years directly managing software and/or ML engineering teams, including hiring, mentoring, and performance management.
Experience partnering cross-functionally with leaders and stakeholders across engineering to prioritize and deliver a shared roadmap.
Strong understanding of simulation, testing, or validation systems for complex, safety-critical software.
Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience.
Experience managing teams that combine traditional software engineering with applied ML or generative AI.
Familiarity with generative models applied to simulation or testing (e.g., traffic-infilling, scenario creation, synthetic data).
Experience building or scaling tools used broadly across a large engineering organization, such as visual editors and agentic authoring tools.
Background in autonomous vehicles, robotics, or another safety-critical, sensor-driven domain.
Track record of leading high-visibility initiatives with executive stakeholders.

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

machine learningmlai

Platform: lever
Effort: quick