Senior Software Engineer, Multiagent Simulation

Job description

Job responsibilities

• Architect high-fidelity multi-robot simulation scenes (terrain, sensors, dynamic obstacles) and scale from single-agent tests to fleet scenarios.
• Integrate physics, perception, and comms models so agents behave realistically at fleet scale.
• Implement and evaluate fleet-level task allocation, coordination, and planning inside simulation.
• Build declarative mission tooling to run thousands of orchestration experiments and profile performance across latency, heterogeneity, and environment complexity.
• Calibrate simulation to real-world telemetry with field teams and reduce the sim-to-real gap.
• Build domain randomization, scenario generation, and automated regression/benchmark gates for fleet orchestration releases.
• Design logging, metrics, and visualization so every run yields actionable data and fleet KPIs (throughput, collisions, comms overhead, idle time).
• Maintain reproducible experiment infrastructure with versioned scenes, configs, and results.
• Partner with perception, planning, learning, DevOps, and infrastructure teams to run large-scale simulation and raise standards for fidelity, coverage, and release quality.

Job requirements

• MS or PhD in Computer Science, Robotics, Aerospace, or a related field (or equivalent industry experience).
• 7+ years hands-on experience building simulation environments for robotics or autonomous systems.
• Proficiency in Python and C++; comfort reading and extending large codebases.
• Working knowledge of robotics simulation engines (e.g., MuJoCo, NVIDIA Isaac Sim, Genesis).
• Experience with multi-robot or multi-agent systems: task allocation, distributed planning, swarm coordination, or fleet management.
• Familiarity with standard robotics middleware.
• Strong problem-solving skills and ability to thrive in fast-paced, interdisciplinary teams.
• Ability to translate research into practical, field-deployable systems.
• Publications or open-source contributions in multiagent systems, multi-robot planning, or fleet coordination (ICRA, RSS, IROS, AAMAS, CoRL).
• Experience with domain randomization, synthetic data generation, or sim-to-real transfer at scale.
• Background in distributed systems or cloud-based simulation orchestration.
• Hands-on work with real robot fleets in field environments (e.g., construction, mining, logistics, defense).Contributions to open-source robotics or simulation frameworks.