Robot Manipulation Engineer

Path Robotics · East Bay

Company

Path Robotics

Location

East Bay

Type

Full Time

Job Description

Build the Path Forward

At Path Robotics, we’re attacking a trillion dollar opportunity - doing things that have never been done before to support an industry hurting from a lack of skilled labor. Big, hard problems are what Path tackles every day and our people are our greatest asset to get that job done. Our intelligent, hardworking team of people do the impossible every single day, yet remain incredibly kind, humble, and always ready to support one another.Β 

We are seeking a skilled and motivated Robot Manipulation Engineer with expertise in modern robotics and manipulation to join our AI - Manipulation team to build agentic AI systems for industrial applications. The ideal candidate will have a strong background in robotics, with a focus on developing and implementing advanced manipulation techniques, motion control systems, and planning algorithms for autonomous robots. This role involves working closely with cross-functional teams to design, test, and deploy innovative solutions that improve the performance and capabilities of our robotic systems.

What You’ll Do

  • Design, develop, and implement advanced manipulation algorithms for robotic systems.
  • Develop, optimize, and deploy learning-based methods for motion control and planning algorithms on a fleet of industrial robotic cells.
  • Implement and refine robotic manipulation strategies to handle complex tasks.
  • Develop and apply behavioral cloning and reinforcement learning (RL) algorithms, including goal-conditioned RL, to solve complex robotic tasks.
  • Collaborate with hardware and software teams to integrate manipulation, control, and planning algorithms into robotic platforms.
  • Conduct simulations and real-world testing to validate the performance of manipulation, control, and planning algorithms.
  • Analyze and troubleshoot issues related to manipulation, motion control, and planning in robotic systems.
  • Stay updated with the latest advancements in robotics, control theory, and planning algorithms.

Who You Are

  • Master's degree or Ph.D. in Robotics, Mechanical Engineering, Electrical Engineering, Computer Science, or a related field.
  • Experience with machine learning techniques applied to fine grained motor control.
  • Strong programming skills in languages such as C++ or Python.
  • Experience with robotic simulation tools (e.g., Isaac Sim, Gazebo, Mojoco).
  • Knowledge of control theory, kinematics, dynamics, and optimization techniques.
  • Familiarity with sensors, actuators, and robotic hardware components.
  • Experience in robot manipulation and behavioral cloning.
  • Proficiency in reinforcement learning (RL) techniques, including goal-conditioned RL.
  • Proven track record of deploying scalable solutions for autonomous robotic systems.
  • Proven track record of publishing impactful work in the robotics field.
  • Excellent problem-solving skills and the ability to work both independently and in a team environment.
  • Strong communication skills, with the ability to convey complex technical concepts to a diverse audience.

Who We Are

At Path Robotics we love coming to work to solve interesting and tough challenges but also because our ideas are welcomed and valued. We encourage unique thinking and are dedicated to creating a diverse and inclusive environment. All qualified applicants will receive consideration for employment without regard to race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.

Why You'll Love It Here

  • Free lunch every day
  • Flexible PTO
  • Medical, Dental and Vision insurance with 100% coverage on monthly medical premiums for you and any dependents on select plans
  • 6 weeks 100% paid parental leave plus an additional 6-8 weeks maternity leave for the
    birthing parent (12-14 weeks total)
  • 401K through Empower
  • Paid Referral Bonus
Apply Now

Date Posted

08/13/2024

Views

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