Engineering Manager - Simulation and Verification

Platform Leadership: Drive the evolution of our simulation platform to support increased scenario throughput, metrics, and scaling.

Team Development: Lead a team of high-performing software engineers and software validation and verification engineers focused on simulation infrastructure, CI/CD pipelines, data verification tools, and scenario creation. You will be responsible for hiring, mentoring, and fostering a culture of technical excellence.

Simulation Strategy: Oversee the development of advanced simulation capabilities, including high-fidelity sensor simulation, closed-loop replay of fleet data, and synthetic scenario generation.

Cross-Functional Collaboration: Partner closely with Planning, Perception, Control, and Safety teams to integrate simulation results into the development lifecycle. Ensure tools and dashboards meet the needs of stakeholders across the organization.

Infrastructure Excellence: Optimize CI/CD workflows to ensure fast, reliable testing. Manage resource allocation to balance high-volume regression testing with on-demand experiment needs.

Process & Quality: Implement rigorous quality control workflows for scenario management. Standardize metrics and benchmark systems to track simulation performance, coverage, and mileage.

Experience: 5+ years in software engineering, with at least 2+ years in an engineering management role.

Technical Domain Expertise: Proven experience in autonomous driving, robotics, or complex system simulation. Proficiency in simulation tools (Carla, Unreal Engine, or custom simulator development).

Core Engineering Skills: Deep experience with modern backend technologies (Python, FastAPI, Postgresql) and frontend frameworks (React, Vite).

Infrastructure Knowledge: Strong understanding of cloud-based development environments (AWS), containerization (Docker, Kubernetes), and CI/CD orchestration (Jenkins).

Data-Driven: Demonstrated ability to build data pipelines that handle high-volume simulation data, including ingestion, storage, and visualization.

Communication: Ability to bridge the gap between complex engineering needs and stakeholder requirements.

Experience with sensor simulation (Lidar/Radar/Camera) and digital twin technologies.

Familiarity with data-driven testing frameworks and large-scale data processing (bag replay, event processing).

Experience in hiring and scaling engineering teams in a fast-paced R&D environment.