Staff Autonomy Simulation Engineer - Aerospace AI Platform

Socket.dev; San Jose (CA); On-site; USD 195,000 - 235,000; Full time

Job summary

Archer, based in San Jose, California, seeks a Staff Autonomy Engineer for its Simulation Platform to bring learned behavior to real aircraft. You will build the simulation and synthetic data platform for testing, evaluating, and training Physical AI systems, including VLA, VLN, and Perception models, supporting both real-world validation and ML workflows.

You will design simulation environments, aircraft dynamics, sensor models, and the orchestration layer; generate synthetic data; and define

Qualifications

• 5+ years in simulation, robotics, or backend infrastructure.
• MS/Ph.D. in Computer Science, Robotics, or related field, or equivalent (exceptional B.S. candidates considered).
• Experience architecting simulation or orchestration/configuration layers across a large codebase.
• Experience building synthetic data and evaluation pipelines.

Responsibilities

• Develop simulation environments, aircraft dynamics, sensor models, and the orchestration layer composing 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.

Skills

Simulation

Robotics

Backend infra

AI methods

Ambiguity tolerance

Safety-focused

Education

MS/PhD in CS/Robotics

Equivalent (exceptional B.S.)

Job description

Archer, based in San Jose, California, seeks a Staff Autonomy Engineer for its Simulation Platform to bring learned behavior to real aircraft. You will build the simulation and synthetic data platform for testing, evaluating, and training Physical AI systems, including VLA, VLN, and Perception models, supporting both real-world validation and ML workflows.

You will design simulation environments, aircraft dynamics, sensor models, and the orchestration layer; generate synthetic data; and define