Senior Robotics Software Engineer - Autonomy

Persona AI

$120K — $145K *
Manufacturing & Automotive
5 - 7 years of experience
Job Overview by Ladders

Qualifications

  • MS or PhD in Robotics, Computer Science, or a related field
  • 5+ years in robotics with a focus on autonomy
  • 2+ years in applying world models for planning and reasoning
  • Experience with behavior trees and state machines
  • World model benchmarking and post-training in robotics
  • Hands-on experience with NVIDIA Cosmos and IsaacSim
  • Proficiency in Python, C++, and CI/CD tools

Responsibilities

  • Design and implement autonomy algorithms for humanoid robots
  • Integrate robot skills into autonomous behaviors with cross-functional teams
  • Develop execution plans combining classical control and learned policies
  • Create reactive, safe, and adaptable behavior execution frameworks
  • Implement data curation pipelines for industrial task understanding
  • Develop synthetic data generation for world model training
  • Establish pipelines for behavior evaluation and regression testing

Benefits

  • Health, dental, and vision insurance
  • Retirement plan with company match
  • Flexible working hours and remote options
  • Professional development and education reimbursement
  • Paid time off and holidays
  • Employee wellness programs
Full Job Description
Job Title: Senior Robotics Software Engineer - Autonomy

Department: Software

Reports To: Behavior Coordination Lead

Employment Type: Full-Time

Location: Houston, TX

Travel: 10%

About the Role

Persona AI is building a rugged humanoid platform to supplement the industrial skilled-labor workforce. Our robots are designed to perform complex tasks such as welding, grinding, and painting in demanding real-world environments.

To succeed, they must understand the job site, translate high-level objectives into executable plans, carry out those plans safely and reactively, and adapt as conditions change. We are looking for aSenior Robotics Software Engineer - Autonomy to help design and build the autonomy stack that enables these capabilities, from simulation through deployment on the shop floor.

This role combines world modeling with proven autonomy techniques to develop intelligent behaviors for humanoids operating at live industrial sites. We train the robot's world model on representative industrial tasks and environments, giving it a deep understanding of the work it must perform. Before each new deployment, we then refine and validate its behavior in a digital twin simulation of the customer's facility to ensure safety, reliability, and performance.

What You Will Be Doing
  • Design and implement autonomy and behavior coordination algorithms for an industrial humanoid platform
  • Work with manipulation, locomotion, and perception engineers to integrate robot skills into autonomous robot behaviors
  • Develop plan execution approaches that combine classical control and learned policies
  • Design and implement behavior execution that is reactive, safe, adaptable, and explainable
  • Implement data curation pipelines that enable our robots to understand a variety of real-world industrial tasks
  • Develop synthetic data generation pipelines for post-training of humanoid world models
  • Design and implement pipelines for autonomous behavior evaluation, benchmarking, and regression testing


What We Are Looking For:
  • MS or PhD in Robotics, Computer Science, or a related field
  • 5+ years of professional experience in robotics, with a primary focus on autonomy
  • 2+ years of experience applying world models to planning, reasoning, and scene understanding
  • Experience with plan execution approaches such as behavior trees and state machines
  • World model benchmarking and post-training experience in a robotics domain
  • Strong hands-on experience with NVIDIA Cosmos and IsaacSim
  • Experience with synthetic data generation, data curation, and benchmark evaluation
  • Strong fundamentals in Python, C++, data structures and algorithms, git, code review, CI/CD


Bonus Skills:
  • Experience using VLMs to generate task plans for autonomous robots
  • Exposure to humanoid robot locomotion, navigation, manipulation, or perception
  • Experience with semantic mapping and scene understanding for autonomous mobile robots
  • Experience with NVIDIA Isaac Lab for reinforcement learning environment setup and training
  • Experience with generative and symbolic planning approaches
  • Experience with ROS2 libraries for autonomous planning and navigation

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