Robotics Technologist III: Stochastic Planning and Control for Field Robotics

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 TechnologistIIIwith advanced skills inmotion control,planning,state estimation, andmachinelearning, as they apply to robotic systemsfor theRobotic Surface Mobility Group, which is part of theRobotic 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 roboticsexpertisefor 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 complexmotion control,planning,and state estimationchallenges across various active projects. The candidate willbe responsible fordevelopingcontrols and planningalgorithms, integrating deep learning models, and designing high-level multi-agent planning frameworks to support robotic operations.

What You'll Do

• Design and implement constraint-aware motion planning and controls formulti-agentsystems.

• Apply deep learning forperception-aware stochastic planning.

• Developlow-levelalgorithmsutilizingmodelpredictive control, reinforcement learning, andgrid-basedorsampling-based planning.

• Develophigher-level planningframeworksincorporatingPartially Observable Markov Decision Processes(POMDP)and actionselectionusing Monte Carlo Tree Search.

• Perform robust robot system integration work with the existingROS2-basedrobotsoftware stacks.

• Support field trials to evaluate autonomous navigation of robotic systems.

Required Qualifications

• Bachelor’s degree in Computer Science, Mechatronics Engineering, or a related discipline with a minimum of 6 years of relevant experience; aMaster’sdegree in a related discipline with a minimum of 4 years of relevant experience; orPh.D. inarelated discipline with a minimum of 2 years of relevant experience.

• Experiencedevelopinguncertainty-aware motion planning and control systems.

• Demonstratedexpertisein estimation theory,simultaneous localization and mapping, and sensor fusion.

• Proficiencyin multi-agent planning and POMDP decision-making frameworks.

• Strong programmingproficiencyin Python,C, andC++.

• Experiencedeveloping and operatingrobot software stacks usingROS2.

• Experienceoperatingand integrating hardware for robotic field expeditions.

• Strong communications skills and ability to work across teams.

Desired Qualifications

• Familiarity with simulation tools for robotic development such as Gazebo,IsaacSim, orMuJoCo.

• Proficiencywith 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.

• Familiarity with diverse sensing modalities (e.g., LiDAR, stereo cameras, IMUs) tailored for resource-constrained or GPS-denied environments.

• Experience in continuous integration and rigorous software testing methodologies (e.g., hardware-in-the-loop,software-in-the-loop) for autonomous operations.

Please provide contact information for three references

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 click Benefits 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.

$149,656 - $186,888

JPL 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.

EEO is the Law.

EEO is the Law Supplement

Pay Transparency Nondiscrimination Provision

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 available here.

This listing was sourced from 4dayweek.io.