Industrial Robot Autonomy Architect

Maven Robotics; San Francisco (CA); On-site; USD 150,000 - 210,000; Full time

Job summary

Maven Robotics is seeking an exceptional Robot Autonomy Engineer to build the decision-making stack that turns goals into coordinated, reliable robot behavior in real industrial applications.

You will own motion planning, behavior planning, and task planning, designing architectures for long-horizon tasks and safe execution on hardware. You’ll coordinate motion across multiple robots, integrating LLMs and VLMs for grounded, verifiable plans, in a fast-paced startup setting.

Qualifications

• MS or PhD in robotics, engineering, mathematics, computer science or a related discipline.
• Real-world experience in classical motion planning for one or more robots — search-based, sampling-based or optimization-based (A*, RRT/PRM, trajectory optimization, model predictive control) — carried onto hardware rather than left in simulation.
• Real-world experience in behavior planning: finite state machines, behavior trees or comparable behavior architectures for long-horizon tasks, including failure detection and recovery.
• Familiarity with task planning in the classical AI planning sense (STRIPS, PDDL, HTN) or decision-theoretic planning (MDP, POMDP), and the judgment to know when that machinery earns its complexity against a simpler reactive design.
• Proficiency in Python and C++ programming, using up-to-date software development practices and tooling.
• Self-starter attitude with strong ability to identify problems, prioritize them, then plan and execute working solutions.
• Enthusiasm for working in a fast paced startup environment and eagerness to support the team on a variety of topics.

Responsibilities

• Own the autonomy stack above the controller — task planning, behavior planning, path planning and trajectory planning — from the moment work arrives to the trajectories handed off to motion control.
• Design the behavior architectures that structure long-horizon manipulation and navigation tasks, and that degrade into retry, recovery and operator handoff rather than into a stall.
• Bring principled task planning to industrial workflows: goal and precedence reasoning, task allocation, and planning under uncertainty.
• Plan and coordinate motion for multiple robots sharing an industrial facility — separation, reservation, deconfliction and deadlock-free repositioning — so that adding a robot adds throughput.
• Integrate LLM and VLM reasoning into planning for task decomposition, subtask grounding and language-conditioned goals, together with the verification and fallbacks that make a model's output safe to execute on real hardware.
• Define the contract between learned policies and classical planning: what the model may decide, what the planner must guarantee, and how the two hand off mid-task.
• Interface with perception, intelligence, controls, simulation and platform software in designing functional architectures that hold up under real-world operation.
• Hold the whole stack to measurable field performance — cycle time, success rate, intervention rate — through simulation, replay of recorded robot logs, and testing on real robots.

Skills

Python

C++

Robotics

Motion planning

Behavior planning

Task planning

Problem solving

Self-starter

Startup mindset

Software development

Education

MS or PhD in robotics

Tools

ROS 2

Drake

OMPL

MoveIt

VDA5050

Job description

Maven Robotics is seeking an exceptional Robot Autonomy Engineer to build the decision-making stack that turns goals into coordinated, reliable robot behavior in real industrial applications.

You will own motion planning, behavior planning, and task planning, designing architectures for long-horizon tasks and safe execution on hardware. You’ll coordinate motion across multiple robots, integrating LLMs and VLMs for grounded, verifiable plans, in a fast-paced startup setting.