
Robotics Technologist II: Learning-Based State Estimation
- 🇺🇸 United States
- 1 day ago
- Machine Learning
- ROS 2
- calibration
- Temporal
- LiDAR
- Python
- C++
- Gazebo
- PyTorch
- TensorFlow
- CUDA
- TensorRT
- CI/CD
- Docker
- Git
Job Details
New ideas are all around us, but only a few will change the world. That’s our focus at JPL. We ask the biggest questions, then search the universe for answers—literally. We build upon ideas that have guided generations, then share our discoveries to inspire generations to come. Your mission—your opportunity—is to seek out the answers that bring us one step closer. If you’re driven to discover, create, and inspire something that lasts a lifetime and beyond, you’re ready for JPL.
Located in Pasadena, California, JPL has a campus-like environment situated on 177 acres in the foothills of the San Gabriel Mountains and offers a work environment unlike any other: we inspire passion, foster innovation, build collaboration, and reward excellence.
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.
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.
Required Qualifications
- 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.
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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.
JPL has a catalog of benefits and perks that span from the traditional to the unique. This includes a variety of health, dental, vision, wellbeing, and retirement plans, paid time off, learning, rideshare, childcare, flexible schedule, parental leave and many more. Our focus is on work-life balance, and living healthy, fulfilling lives as we Dare Mighty Things Together. For benefits eligible positions, benefits are effective the first day of the month coincident with or immediately following the employee’s start date.
For further benefits information clickBenefits and Perks
The hiring range displayed below is specifically for those who will work in or reside in the location listed. In extending an offer, Jet Propulsion Laboratory considers factors including, but not limited to, the candidate’s job related skills, experience, knowledge, and relevant education/training.
The typical full time equivalent annual hiring range for this job in Pasadena, California.
$122,408 - $150,384JPL is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to sex, race, color, religion, national origin, citizenship, ancestry, age, marital status, physical or mental disability, medical condition, genetic information, pregnancy or perceived pregnancy, gender, gender identity, gender expression, sexual orientation, protected military or veteran status or any other characteristic or condition protected by Federal, state or local law.
In addition, JPL is a VEVRAA Federal Contractor.
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The Jet Propulsion Laboratory is a federal facility. Due to rules imposed by NASA, JPL will not accept applications from citizens of designated countries or those born in a designated country unless they are U.S. Citizens, Legal Permanent Residents of the U.S or have other protected status under 8 U.S.C. 1324b(a)(3). The Designated Countries List is availablehere.
Robotics Technologist II: Learning-Based State Estimation · California Institute Of Technology Jet Propulsion Laboratory