FieldAI · 55 minutes ago
1.2 Multi-agent AI Research Engineer: Scalable Robot Fleet Coordination
Boston, MA
Full-time
Hybrid
Senior Level
$70K/yr - $300K/yrField AI is transforming how robots interact with the real world by building reliable AI systems for complex challenges in robotics. The Multi-Robot Intelligence Research Engineer will design and implement scalable algorithms for coordination and decision-making in multi-robot systems, focusing on decentralized control and game-theoretic approaches.
Enterprise SoftwareRobotic Process Automation (RPA)Robotics
Responsibilities
Develop fundamental algorithms for multi-agent coordination (including differentiable game theory, mean-field control, and decentralized optimization) to enable fleets of autonomous robots to operate in real-world, high-stakes environments
Design computationally tractable formulations of multi-agent Nash equilibria, Stackelberg games, and cooperative decision-making strategies, ensuring robust and scalable decision-making across heterogeneous robotic teams
Build predictive models for multi-agent interaction dynamics, leveraging graph-based learning and control-theoretic formulations to drive efficient coordination in dynamic, adversarial, and uncertain settings
Develop distributed inference and control policies using neural PDEs, mean-field game-theoretic methods, and scalable stochastic optimization for real-time at-scale robotic interaction
Bridge theory with deployment —integrate multi-agent planning, auction-based task allocation, and decentralized multiagent reinforcement learning (MARL) into hardware-in-the-loop robotic systems operating at scale
Push the limits of explainability in multi-agent AI, ensuring tractability, convergence guarantees, and real-world feasibility while maintaining risk-aware and uncertainty-resolving decision-making
Collaborate across teams to transition multi-agent models from high-fidelity simulations to real-world deployments, working alongside robotics engineers, AI/ML researchers, and field roboticists to ensure seamless real-world operation
Qualification
Required
Ph.D. in Applied Mathematics, Game Theory, Control Theory, Computer Science, or a related field, with expertise in multi-agent decision-making and coordination algorithms
Deep understanding of game-theoretic methods —including differential games, Nash equilibria, mean-field games, and Stackelberg equilibria —with a focus on scalability and tractability
Experience with multi-agent RL (MARL) and distributed optimization for large-scale robotic coordination in imperfect information settings
Hands-on experience implementing multi-agent algorithms in real-time robotic or AI-driven systems, with exposure to hardware constraints, real-world latency, and stochastic disturbances
Proficiency in Python, C++, or Julia, with experience in optimization libraries (e.g., CVXPY, Gurobi, JAX), reinforcement learning frameworks (e.g., RLlib, Acme), and multi-robot simulators
Ability to transition theoretical insights into scalable, field-deployable systems, ensuring robustness under uncertainty and adaptability to real-world constraints
Preferred
Experience working with large-scale robotic coordination (e.g., drone swarms, autonomous fleets, or industrial automation systems) is a strong plus
Company
FieldAI
FieldAI is pioneering the development of a field-proven, hardware agnostic brain technology that enables many different types of robots to operate autonomously in hazardous, offroad, and potentially harsh industrial settings – all without GPS, maps, or any pre-programmed routes.
Founded in 2023
11-50 employees
H1B Sponsorship
FieldAI has a track record of offering H1B sponsorships. Please note that this does not
guarantee sponsorship for this specific role. Below presents additional info for your
reference. (Data Powered by US Department of Labor)
Distribution of Different Job Fields Receiving Sponsorship
Represents job field similar to this job
Trends of Total Sponsorships
2025 (9)
Funding
Current Stage
Early StageTotal Funding
$405M2025-08-20Series Unknown· $91M
2025-08-20Series A· $314M
Leadership Team
Ali Agha
Founder and CEO
Recent News
Crunchbase News
2025-12-19
2025-10-16
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