We offer:

• Career Development
• Competitive Compensation and Benefits
• Pay Transparency
• Global Opportunities
  

Learn More Here: provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race color religion age sex national origin disability status genetics protected veteran status sexual orientation gender identity or expression or any other characteristic protected by federal state or local laws.

This policy applies to all terms and conditions of employment including recruiting hiring placement promotion termination layoff recall transfer leaves of absence compensation and training.

The base pay range for this role is estimated to be $19.00 - $23.00 per hour at the time of posting. Final compensation will be determined by various factors such as work location education experience knowledge and skills.

Tasks and Qualifications:

What Makes This Role Unique

• Work on real industrial autonomous vehicles not just simulations
• Solve production-grade autonomy problems in challenging environments
• Influence systems that are deployed at scale in logistics and automation
• Collaborate with experienced robotics engineers bridging research and production
  

What You Will Do in this Role:

• Design implement and evaluate advanced SLAM and localization algorithms
• Work within and extend ROS2-based real-time systems
• Deploy and validate algorithms on real AGV platforms analyzing performance in dynamic industrial environments
• Build simulation and validation tools
• Collaborate with production engineering teams to transition research into robust deployable solutions
• Document experimental methodology analyze results and present insights to technical stakeholders

What We are Looking For:

• Pursuing a degree in Computer Science Robotics Electrical/Mechanical Engineering or related field (GPA 3.0)
• Strong programming skills in at least one of the following programming languages: C Python or Rust
• Solid understanding of:
  • Robotics fundamentals (kinematics coordinate frames transforms)
  • Linear algebra probability and optimization
    

Preferred (Strong Differentiators):

• Hands-on experience with:
  • SLAM systems (graph-based SLAM visual SLAM LiDAR SLAM)
  • Factor graphs and pose graph optimization (GTSAM g2o)
  • State estimation techniques (KF EKF UKF)
  • Sensor fusion (LiDAR IMU wheel odometry)
• Experience with ROS2 including node architecture and real-time pipelines
• Exposure to:
  • Simulation environments (Gazebo Isaac or similar)
  • Robotics testing methodologies (Monte Carlo validation regression testing)
• Prior academic or personal projects in autonomous systems robotics or computer vision
  

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