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# Robotics Technologist II: Learning-Based State Estimation

- **Company:** NASA JPL
- **Location:** Pasadena, CA, United States
- **Salary:** $122,408.0 - $150,384.0
- **Contract:** Permanent contract
- **Skills:** C (Programming Language), Computer Vision, C++ (Programming Language), Nvidia CUDA, Computer Programming, Continuous Integration, Programming Tools, Hardware-In-The-Loop Simulation, Python (Programming Language), Tensorflow, State Estimation, Robotic Automation Software, Sensor Fusion, Systems Integration, Pytorch, Mobile Robots, Deep Learning, Git, Information Technology, TensorRT, Lidar, GNSS, Docker
- **Published:** October 13, 2026
- **Apply:** https://www.indeed.com/viewjob?jk=8fa8cd20dd28f016

## About the Role

Wanted: A Robotics Technologist II with advanced skills in motion control, planning, state estimation, and machine learning, as they apply to robotic systems for the Robotic Surface Mobility Group, which is part of the Robotic Mobility and Manipulation Section., * Bachelor's degree in Computer Science, Mechatronics Engineering, or a related discipline with a minimum of 3 years of experience; a Master's degree in a related discipline with a minimum of 1 years of experience; or Ph.D. in a related discipline with a minimum of 0 years of relevant experience.

 * Demonstrated expertise in estimation theory, simultaneous localization and mapping, and/or sensor fusion.
 * Experience developing and implementing state estimation algorithms (e.g. EKF, MSCKF, factor graph) on hardware.
 * Experience with multi-sensor calibration for spatial and temporal offsets.
 * Familiarity with diverse sensing modalities (e.g., LiDAR, stereo cameras, IMUs) tailored for resource-constrained or GNSS-denied environments.
 * Strong programming proficiency in Python, C, and C++.
 * Experience developing and operating robot software stacks using ROS2.
 * Experience operating and integrating hardware for robotic field expeditions.
 * Strong communications skills and ability to work across teams.

Desired Qualifications

 * Familiarity training, fine tuning or integrating large vision models
 * Familiarity with simulation tools for robotic development such as Gazebo, IsaacSim, or MuJoCo.
 * Proficiency with modern machine learning frameworks (e.g., PyTorch, TensorFlow) for training and deploying perception and vision models.
 * Experience with compute optimization and GPU acceleration (e.g., CUDA, TensorRT) for real-time, onboard robotic processing.
 * Experience in continuous integration and rigorous software testing methodologies (e.g., hardware-in-the-loop, software-in-the-loop) and development tools (e.g. Docker, Git) for autonomous operations.

## Description

The Robotics section develops, matures, and brings to space flight, robotics technology for in-situ exploration of the solar system. The Section also provides robotics expertise for space flight hardware and software implementation along with mission operations support.

Opportunity: To work with an enthusiastic multi-disciplinary workforce that originates and executes robotics technology development and space flight projects. This role is highly focused on addressing state estimation challenges across various active projects. The candidate will be responsible for developing learning-based state estimation algorithms, integrating and fusing a disparate set of sensing modalities, and evaluating state estimation for robotic operations in GNSS-denied environments.

What You'll Do

 * Design and implement state estimation systems for autonomous operations of mobile robots in extreme environments.
 * Apply deep learning for state estimation.
 * Evaluate multiple disparate sensing modalities and their fusion for generating localization and mapping solutions.
 * Integrate and calibrate multi-sensor systems with robotic hardware.
 * Perform robust robot system integration work with the existing ROS2-based robot software stacks.
 * Evaluate autonomous operations of these robotic systems in the field.