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AI Robot Fleet Coordination Developer

Riley Magnusson

Full-time · Job · Los_Angeles

About the role

One robot picking items in a warehouse is a control problem. Forty robots picking items simultaneously without colliding, blocking each other's paths, or competing for the same items is a multi-agent coordination problem that gets exponentially harder as the fleet grows. Our coordination system manages fleets of up to 100 autonomous mobile robots, optimizing collective throughput while preventing deadlocks and collisions. The coordination challenge combines task assignment (which robot picks which item), path planning (how does each robot get there without blocking others), and dynamic replanning (what happens when a robot encounters an obstacle or fails mid-task). You'll build the multi-agent planning system that solves these problems jointly rather than independently, because locally optimal individual plans often produce globally terrible fleet performance. You'll work 3 days per week at our Palo Alto robotics lab where we have a 50-robot test fleet on a warehouse-scale floor. The robotics team is 15 engineers; you'll lead the fleet coordination module.

Responsibilities

  • Design multi-agent coordination for fleets of up to 100 mobile robots
  • Build joint task assignment and path planning optimization
  • Implement dynamic replanning for obstacle avoidance and robot failures
  • Prevent deadlocks and congestion in shared warehouse spaces
  • Optimize collective fleet throughput rather than individual robot performance
  • Validate coordination strategies on 50-robot physical test fleet

Requirements

  • 6+ years in robotics or multi-agent systems with fleet coordination experience
  • Deep expertise in multi-agent planning and coordination algorithms
  • Experience with reinforcement learning for multi-agent optimization
  • Strong Python and PyTorch skills
  • Comfort working with physical robot fleets in warehouse environments

Benefits

  • Hybrid — 3 days Palo Alto lab, flexible remote
  • Top-of-market compensation plus equity
  • Health, dental, vision, and life insurance
  • $5,000 annual conference budget
  • Lead fleet coordination for warehouse automation

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Categories

AI & Machine Learning Engineers Automation & AI Workflows

Skills

python pytorch reinforcement learning docker aws

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Job Type

Full-time

Level

Senior

Language

English

Salary Range

$160k – $200k / year

AI Expertise

AI & Machine Learning Engineers Automation & AI Workflows

Skills

python pytorch reinforcement learning docker aws

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