Senior Multi-Agent Robotics Simulation Engineer

Field AI; Boston (MA); On-site; USD 125,000 - 170,000; Full time

Benefits offered by this job

Equity participation

Comprehensive benefits

Opportunity to contribute to cutting‑e

Job summary

FieldAI is transforming how robots interact with the real world. Our growing R&D team is based in Boston, where we develop risk-aware, reliable, field-ready AI systems that tackle the hardest problems in robotics and unlock the potential of embodied intelligence.

We take a pragmatic approach that goes beyond off-the-shelf, purely data-driven methods or transformer-only architectures, combining cutting-edge research with real-world deployment.

Qualifications

• 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.

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.

Skills

Python

C++

Robotics simulation

Multi-robot systems

Distributed planning

Robotics middleware familiarity

Problem solving

Education

MS or PhD in Computer Science, Robotics, Aerospace, or related field

Tools

MuJoCo

NVIDIA Isaac Sim

Genesis

ROS

Job description

FieldAI is transforming how robots interact with the real world. Our growing R&D team is based in Boston, where we develop risk-aware, reliable, field-ready AI systems that tackle the hardest problems in robotics and unlock the potential of embodied intelligence.

We take a pragmatic approach that goes beyond off-the-shelf, purely data-driven methods or transformer-only architectures, combining cutting-edge research with real-world deployment.