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Archer Technologies is building an all-electric vertical takeoff and landing (eVTOL) aircraft based in San Jose, California. The company is designing, manufacturing, and operating aircraft that can carry four passengers while producing minimal noise, advancing sustainable air mobility.
As a Staff Autonomy Engineer on the Simulation Platform team, you will play a central role in bringing learned, intelligent behavior to real aircraft. You'll architect and build the simulation and synthetic data platform used to test, evaluate, and train Physical AI systems—including Vision Language Action (VLA), Vision Language Navigation (VLN), and Perception models—supporting both real-world validation and machine learning training workflows.
Key responsibilities include:
- Develop simulation environments, aircraft dynamics models, sensor models, and the orchestration layer that composes scenarios and missions
- Build tooling for large-scale, procedural, automated scenario generation and rendering
- Generate synthetic sensor and telemetry data for physical AI training via physics-based rendering
- Define evaluation metrics that turn simulation output into data-driven decisions
- Partner with flight test teams to keep simulated scenarios grounded in real-world conditions
- Set platform architecture and roadmap ahead of team growth
You'll need 5+ years of experience in simulation, robotics, or backend infrastructure, with an M.S./Ph.D. in Computer Science, Robotics, or related field (or equivalent). You should have demonstrated experience architecting simulation or orchestration/configuration layers across large codebases, building synthetic data and evaluation pipelines, and working knowledge of AI development methods including data flywheels and eval-driven iteration. Comfort with ambiguity, evolving scopes, and interest in safety-critical, regulated engineering are essential.
Bonus qualifications include neural rendering or generative AI for synthetic data (e.g., Gaussian Splatting), integrating heterogeneous data sources, simulation for embodied/physical AI systems, flight dynamics and 6-DOF simulation experience, and background in safety-critical or regulated engineering (aerospace, automotive, medical devices).
