{"schemaVersion":"jobsearcher.job.v1","id":"e15fa62e4968f585d0f8cd48","url":"https://jobsearcher.com/jobs/e15fa62e4968f585d0f8cd48","canonicalUrl":"https://jobsearcher.com/jobs/e15fa62e4968f585d0f8cd48","title":"Robotics Simulation & Controls Intern","description":"Robotics Simulation & Controls Intern — Isaac Sim / Isaac LabLocation: San Jose, CAType: Internship – part time (up to 30 hours per week) temporaryDuration: expected 12 weeksStart: Summer 2026 or flexibleEligible candidates: Current B.S./M.S. students, recent graduates, or strong project-based candidates in Robotics, Mechatronics, Mechanical Engineering, Computer Engineering, Electrical Engineering, Computer Science, or related fields.About the RoleWe are seeking a Robotics Simulation & Controls Intern to support an early-stage robotics R&D effort focused on simulation, control development, and sim-to-real transfer for legged robotic systems.The initial focus will be to help build a practical NVIDIA Isaac Sim / Isaac Lab workflow that can support robot modeling, reinforcement-learning experiments, actuator/sensor approximation, and eventual transfer from simulation to physical hardware. Depending on project needs, early work may use a simplified legged test platform, reduced-order robot model, or DOE simulation before scaling the workflow to more complex robotic systems.This is a hands-on R&D role for someone who enjoys learning quickly, reading technical documentation, building prototypes, and working across robotics, software, simulation, controls, and mechanical systems.What You Will DoHelp set up and document the NVIDIA Isaac Sim / Isaac Lab development environment.Build or adapt robot simulation assets using CAD, URDF, USD, or related robot-description workflows.Define joints, joint axes, joint limits, collision geometry, approximate mass/inertia properties, and sensor placements.Support the creation of simplified legged robot models for early simulation and control testing.Help develop basic reinforcement-learning or control experiments for flat-terrain standing, balancing, or walking behavior.Work on observation/action space design using signals such as joint position, joint velocity, IMU data, command inputs, contact assumptions, and prior actions.Assist with reward design, termination conditions, domain randomization, and evaluation criteria for sim-to-real transfer.Evaluate whether ROS 2, Gazebo, Isaac Sim ROS bridges, or a custom interface should be used for different stages of the workflow.Help document model assumptions, training results, known simulation gaps, and next-step recommendations.Use tools such as ChatGPT Business, Microsoft Copilot Premium, and Github Copilot to accelerate research, coding, documentation, and troubleshooting while carefully validating technical results.Ideal BackgroundStrong candidates may come from Robotics, Mechatronics, Mechanical Engineering, Computer Engineering, Electrical Engineering, Computer Science, or a related technical program.The ideal candidate has some combination of:Python programming experience.Basic C/C++ familiarity or willingness to learn.Coursework or projects involving robotics, controls, dynamics, simulation, machine learning, reinforcement learning, autonomous systems, or mechatronics.Familiarity with one or more robotics simulation tools such as Isaac Sim, Isaac Lab, Omniverse, Gazebo, MuJoCo, or similar.Familiarity with one or more robotics/software tools such as ROS 2, URDF, or USD.Comfort reading documentation, testing examples, debugging errors, and turning technical goals into working prototypes.Strong written documentation habits.Nice to HaveExperience with legged robots, quadrupeds, bipeds, mobile robots, robot arms, or autonomous robotics projects.Exposure to reinforcement learning, imitation learning, motion planning, trajectory optimization, or model-predictive control.Understanding of coordinate frames, rigid-body dynamics, center of mass, friction, contact, joint limits, and actuator constraints.Experience with ROS 2, Gazebo, Isaac Sim, Isaac Lab, MuJoCo, or similar robotics simulation environments.Experience with Raspberry Pi, embedded Linux, serial communication, I2C, IMUs, servo motors, motor controllers, or sensor integration.CAD exposure using SolidWorks, Siemens NX, Fusion 360, Onshape, or similar.Experience with 3D printing or physical robot prototyping.Experience using AI tools such as ChatGPT, Copilot, or similar systems as part of an engineering workflow.What Success Looks LikeBy the end of the internship, a successful candidate will have helped create:A documented Isaac Sim / Isaac Lab setup that can be reproduced.One or more simplified robot simulation models suitable for controls or reinforcement-learning experiments.A clear CAD / URDF / USD workflow recommendation.A first-pass control or reinforcement-learning experiment for simple flat-terrain legged locomotion or balancing.A documented list of simulation assumptions, actuator/sensor modeling gaps, and sim-to-real risks.A practical roadmap for moving from simulated training toward controlled physical testing.Desired TraitsCurious, self-directed, and comfortable learning unfamiliar tools.Strong problem-solving and debugging mindset.Able to work with incomplete specifications in an R&D environment.Careful around hardware, safety, and electromechanical systems.Good communicator who can explain what was tried, what worked, what failed, and what should be done next.Suggested LinkedIn SkillsRobotics, Legged Robotics, Robot Simulation, Controls, Reinforcement Learning, Isaac Sim, Isaac Lab, NVIDIA Omniverse, Sim-to-Real, ROS 2, Gazebo, MuJoCo, Python, C++, PyTorch, URDF, USD, Mechatronics, Dynamics, Motion Control, Embedded Systems, Raspberry Pi, IMU, CADCompensation and BenefitsHourly Rate: $25–$45 per hour, depending on education, experience, technical skills, and demonstrated robotics or simulation project experience401K with company match.Eugenus, Inc. is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.","company":"Eugenus","rawCompany":"eugenus","city":"San Jose","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-07-03T10:09:48.942Z","occupations":[{"code":"17-2199.08","title":"Robotics Engineers","slug":"robotics-engineers"},{"code":"17-3024.01","title":"Robotics Technicians","slug":"robotics-technicians"},{"code":"17-2199.05","title":"Mechatronics Engineers","slug":"mechatronics-engineers"}],"industries":[{"code":"541715","title":"Research and Development in the Physical, Engineering, and Life Sciences (except Nanotechnology and Biotechnology)","slug":"research-and-development-in-the-physical-engineering-and-life-sciences-except-nanotechnology-and-biotechnology"},{"code":"541330","title":"Engineering Services","slug":"engineering-services"},{"code":"333248","title":"All Other Industrial Machinery Manufacturing","slug":"all-other-industrial-machinery-manufacturing"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Robotics Simulation & Controls Intern","description":"Robotics Simulation & Controls Intern — Isaac Sim / Isaac LabLocation: San Jose, CAType: Internship – part time (up to 30 hours per week) temporaryDuration: expected 12 weeksStart: Summer 2026 or flexibleEligible candidates: Current B.S./M.S. students, recent graduates, or strong project-based candidates in Robotics, Mechatronics, Mechanical Engineering, Computer Engineering, Electrical Engineering, Computer Science, or related fields.About the RoleWe are seeking a Robotics Simulation & Controls Intern to support an early-stage robotics R&D effort focused on simulation, control development, and sim-to-real transfer for legged robotic systems.The initial focus will be to help build a practical NVIDIA Isaac Sim / Isaac Lab workflow that can support robot modeling, reinforcement-learning experiments, actuator/sensor approximation, and eventual transfer from simulation to physical hardware. Depending on project needs, early work may use a simplified legged test platform, reduced-order robot model, or DOE simulation before scaling the workflow to more complex robotic systems.This is a hands-on R&D role for someone who enjoys learning quickly, reading technical documentation, building prototypes, and working across robotics, software, simulation, controls, and mechanical systems.What You Will DoHelp set up and document the NVIDIA Isaac Sim / Isaac Lab development environment.Build or adapt robot simulation assets using CAD, URDF, USD, or related robot-description workflows.Define joints, joint axes, joint limits, collision geometry, approximate mass/inertia properties, and sensor placements.Support the creation of simplified legged robot models for early simulation and control testing.Help develop basic reinforcement-learning or control experiments for flat-terrain standing, balancing, or walking behavior.Work on observation/action space design using signals such as joint position, joint velocity, IMU data, command inputs, contact assumptions, and prior actions.Assist with reward design, termination conditions, domain randomization, and evaluation criteria for sim-to-real transfer.Evaluate whether ROS 2, Gazebo, Isaac Sim ROS bridges, or a custom interface should be used for different stages of the workflow.Help document model assumptions, training results, known simulation gaps, and next-step recommendations.Use tools such as ChatGPT Business, Microsoft Copilot Premium, and Github Copilot to accelerate research, coding, documentation, and troubleshooting while carefully validating technical results.Ideal BackgroundStrong candidates may come from Robotics, Mechatronics, Mechanical Engineering, Computer Engineering, Electrical Engineering, Computer Science, or a related technical program.The ideal candidate has some combination of:Python programming experience.Basic C/C++ familiarity or willingness to learn.Coursework or projects involving robotics, controls, dynamics, simulation, machine learning, reinforcement learning, autonomous systems, or mechatronics.Familiarity with one or more robotics simulation tools such as Isaac Sim, Isaac Lab, Omniverse, Gazebo, MuJoCo, or similar.Familiarity with one or more robotics/software tools such as ROS 2, URDF, or USD.Comfort reading documentation, testing examples, debugging errors, and turning technical goals into working prototypes.Strong written documentation habits.Nice to HaveExperience with legged robots, quadrupeds, bipeds, mobile robots, robot arms, or autonomous robotics projects.Exposure to reinforcement learning, imitation learning, motion planning, trajectory optimization, or model-predictive control.Understanding of coordinate frames, rigid-body dynamics, center of mass, friction, contact, joint limits, and actuator constraints.Experience with ROS 2, Gazebo, Isaac Sim, Isaac Lab, MuJoCo, or similar robotics simulation environments.Experience with Raspberry Pi, embedded Linux, serial communication, I2C, IMUs, servo motors, motor controllers, or sensor integration.CAD exposure using SolidWorks, Siemens NX, Fusion 360, Onshape, or similar.Experience with 3D printing or physical robot prototyping.Experience using AI tools such as ChatGPT, Copilot, or similar systems as part of an engineering workflow.What Success Looks LikeBy the end of the internship, a successful candidate will have helped create:A documented Isaac Sim / Isaac Lab setup that can be reproduced.One or more simplified robot simulation models suitable for controls or reinforcement-learning experiments.A clear CAD / URDF / USD workflow recommendation.A first-pass control or reinforcement-learning experiment for simple flat-terrain legged locomotion or balancing.A documented list of simulation assumptions, actuator/sensor modeling gaps, and sim-to-real risks.A practical roadmap for moving from simulated training toward controlled physical testing.Desired TraitsCurious, self-directed, and comfortable learning unfamiliar tools.Strong problem-solving and debugging mindset.Able to work with incomplete specifications in an R&D environment.Careful around hardware, safety, and electromechanical systems.Good communicator who can explain what was tried, what worked, what failed, and what should be done next.Suggested LinkedIn SkillsRobotics, Legged Robotics, Robot Simulation, Controls, Reinforcement Learning, Isaac Sim, Isaac Lab, NVIDIA Omniverse, Sim-to-Real, ROS 2, Gazebo, MuJoCo, Python, C++, PyTorch, URDF, USD, Mechatronics, Dynamics, Motion Control, Embedded Systems, Raspberry Pi, IMU, CADCompensation and BenefitsHourly Rate: $25–$45 per hour, depending on education, experience, technical skills, and demonstrated robotics or simulation project experience401K with company match.Eugenus, Inc. is an Equal Opportunity Employer. Qualified applicants will receive consideration for employment without regard to race, color, national origin, citizenship, ancestry, religion, creed, sex, sexual orientation, gender identity, age, disability, veteran or military status, or any other basis prohibited by law.","datePosted":"2026-07-03T10:09:48.942Z","dateModified":"2026-07-03T10:09:48.942Z","hiringOrganization":{"@type":"Organization","name":"Eugenus","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"San Jose","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"e15fa62e4968f585d0f8cd48"},"url":"https://jobsearcher.com/jobs/e15fa62e4968f585d0f8cd48"}}