ZipRecruiter

Log In

1

Internship Robotics Simulator Jobs in California

Amazon

Senior Robotics SDE, Safe Autonomy, Compass

Pasadena, CA · On-site

$133K - $176K/yr

BASIC QUALIFICATIONS - 5+ years of non-internship professional software development experience - 5+ ... simulation environments for robotics - Strong communication skills and experience working in cross ...

Atomic Machines

Systems Engineer

Emeryville, CA · On-site

Help develop and maintain system models used for analysis and simulation. * Work hands-on with ... What You'll Need: * 3+ years of experience (industry, internships, robotics competitions, IEEE ...

Pronto

Robotics Controls Engineer

San Francisco, CA · On-site

$119K - $161K/yr

Analyze system performance through simulation and field testing * Debug control issues using logged ... internship) software development experience * Strong foundation in classical control theory (PID ...

1X Technologies AS

AI Residency

San Carlos, CA · On-site

$10K/mo

Residents work on real projects-simulation infrastructure, data management, model evaluation, and capability deployment-that ship to production robots in the field. This is not an internship where ...

next page

Showing results 1-20

All JobsRobotics Simulator JobsInternship Robotics Simulator JobsInternship Robotics Simulator Jobs in California

Internship Robotics Simulator information

What is the difference between Internship Robotics Simulator vs Robotics Engineer?

AspectInternship Robotics SimulatorRobotics Engineer
CredentialsEnrolled in or recent graduate of engineering or computer science programsBachelor's or master's degree in robotics, mechanical, electrical, or computer engineering
Work EnvironmentEducational or training settings, simulation labs, or remoteResearch labs, manufacturing facilities, or corporate offices
Industry UsageLearning and training in robotics simulation softwareDesign, develop, and test real robotic systems

The Internship Robotics Simulator role focuses on gaining experience through simulation tools and educational environments, while Robotics Engineers work on designing and implementing actual robotic systems in professional settings. Both roles share foundational knowledge but differ in scope and responsibilities.

What does an Internship Robotics Simulator do?

An Internship Robotics Simulator typically involves working with software that models the behavior of robots in virtual environments. Interns in this role help design, develop, and test robotics simulations to evaluate algorithms, sensor integrations, or robot movements without needing physical hardware. This allows for rapid prototyping, debugging, and validation of robotic systems. Interns may assist engineers by creating simulation scenarios, analyzing results, and improving simulation fidelity. The role is ideal for students or recent graduates interested in robotics, computer science, or related engineering disciplines.

What are the key skills and qualifications needed to thrive as an Internship Robotics Simulator, and why are they important?

To excel as an Internship Robotics Simulator, you need a background in robotics, mechanical or electrical engineering, and programming fundamentals, often supported by current enrollment in a relevant degree program. Familiarity with simulation tools like Gazebo, MATLAB/Simulink, or ROS, as well as coding languages such as Python or C++, is typically required. Strong problem-solving abilities, attention to detail, and effective teamwork are soft skills that help interns stand out. These competencies are essential for accurately modeling robotic systems, collaborating on innovative projects, and translating simulated results into real-world applications.

What types of projects or tasks can I expect to work on during an internship in robotics simulation?

As an intern in robotics simulation, you'll typically work on developing, testing, and troubleshooting virtual models of robots within simulation environments like Gazebo, ROS, or V-REP. Your tasks may include writing scripts to automate robot behaviors, creating and refining simulation scenarios, and assisting in integrating sensors or actuators into simulated robots. Expect close collaboration with engineers and researchers, as you'll often help validate algorithms before they're tested on real hardware. This hands-on experience provides valuable exposure to both software development and robotics engineering challenges.
What are the most commonly searched types of Robotics Simulator jobs in California? The most popular types of Robotics Simulator jobs in California are:
What are popular job titles related to Internship Robotics Simulator jobs in California? For Internship Robotics Simulator jobs in California, the most frequently searched job titles are:
What job categories do people searching Internship Robotics Simulator jobs in California look for? The top searched job categories for Internship Robotics Simulator jobs in California are:
What cities in California are hiring for Internship Robotics Simulator jobs? Cities in California with the most Internship Robotics Simulator job openings:
Internship Robotics Simulator jobs near you
Infographic showing various Internship Robotics Simulator job openings in California as of July 2026, with employment types broken down into 33% Internship, 50% Full Time, and 17% Part Time. Highlights an 83% In-person, and 17% Remote job distribution.

AI Robotics Researcher Intern (Dexterous Manipulation)

NIO

San Jose, CA • On-site

Full-time

Re-posted 2 days ago

Job description

JOB DESCRIPTION
About NIO
NIO is a pioneer and a leading company in the premium smart electric vehicle market. Founded in November 2014, NIO's mission is to shape a joyful lifestyle. NIO aims to build a community starting with smart electric vehicles to share joy and grow together with users.
NIO designs, develops, jointly manufactures and sells premium smart electric vehicles, driving innovations in next-generation technologies in autonomous driving, digital technologies, electric powertrains and batteries. NIO differentiates itself through its continuous technological breakthroughs and innovations, such as its industry-leading battery swapping technologies, Battery as a Service, or BaaS, as well as its proprietary autonomous driving technologies and Autonomous Driving as a Service, or ADaaS.
NIO's product portfolio consists of the ES8, a six-seater smart electric flagship SUV, the ES7 (or the EL7), a mid-large five-seater smart electric SUV, the ES6, a five-seater all-round smart electric SUV, the EC7, a five-seater smart electric flagship coupe SUV, the EC6, a five-seater smart electric coupe SUV, the ET7, a smart electric flagship sedan, and the ET5, a mid-size smart electric sedan.
About the Position
We are looking for an outstanding AI Robotics Research Intern to join the team at NIO. This role operates at the cutting edge of embodied AI and dexterous manipulation, with a specific focus on utilizing large-scale foundation models and human data-based learning to empower robots with physical world intelligence.
As an intern, you will tackle the fundamental challenges of dexterous manipulation by harvesting human-object interaction data from diverse sources-ranging from unstructured web videos to high-fidelity human glove-collected data. Your work will involve translating these rich human insights into executable robotic behaviors, bridging the gap between human dexterity and machine execution. You will be responsible for deploying these policies on real hardware, to perform complex, contact-rich tasks in real-world environments
Project Scope
  • Learning from Human Demonstrations: Develop and refine scalable frameworks for the transfer of human-object interaction skills to diverse robotic embodiments.
  • Large-Scale Data Synthesis: Architect autonomous pipelines to process vast amounts of visual data and human glove-collected data, extracting the spatial and contact-rich information necessary for generalist robot training.
  • GenerativeEmbodied AI: Implement state-of-the-art generative architectures to synthesize physically grounded, high-fidelity trajectories based on human reference motions.
  • Unified Policy Training: Explore cross-embodiment representations that enable joint training on human and robot data to improve generalization in unstructured environments.
  • Sim-to-Real Deployment: Research and optimize distillation and retargeting techniques to bridge the gap between simulation-trained policies and physical robotic deployment.
  • Semantic Scene Understanding: Utilize vision-language foundation models to autonomously segment skills and extract task-relevant parameters from complex human activities.
Deliverables (End of Internship)
  • A robust pipeline for converting human multi-modal data into actionable robot motor skills.
  • A successful sim-to-real validation of a dexterous manipulation policy on a physical humanoid or multi-fingered platform.
  • A high-quality technical manuscript or demo suitable for internal review or submission to a top-tier robotics conference.

Qualifications
  • Master's or Ph.D. in Robotics, Computer Science, Artificial Intelligence, Mechanical/Electrical Engineering, or related fields.
  • Strong technical foundation in robot learning and control, including areas such as reinforcement learning, imitation learning, world modeling, or representation learning for agent-environment interactions.
  • Practical experience implementing and fine-tuning Generative Models and Transformer architectures.
  • Hands-on experience with robotic manipulation systems, particularly involving contact-rich interaction, grasping, or multi-sensor perception (e.g., tactile, force/torque, proprioception).
  • Proficiency in Python and modern ML frameworks (e.g., PyTorch, JAX, TensorFlow), with experience using robotics middleware or simulation tools (e.g., ROS/ROS2, MuJoCo, Isaac Sim, PyBullet).
  • Demonstrated ability to implement, experiment, and iterate on research ideas, including evaluating methods through empirical results on simulated or physical robotic systems.
  • Strong analytical and system-building skills, with the ability to work across simulation, learning, perception, control, and real robot deployment as part of a larger technical team.

Preferred Qualifications
  • Ph.D. (or Ph.D. candidate expecting graduation within 6-12 months).
  • Prior experience with dexterous manipulation, multi-finger robotic hands, in-hand manipulation, or grasp optimization beyond parallel-jaw grasping.
  • Experience deploying learning-based policies on real robotic hardware, including exposure to sim-to-real transfer challenges such as contact mismatch, compliance, sensing noise, or latency.
  • Familiarity with contact modeling, tactile sensing, force/torque feedback, or low-level control interfaces for manipulation.
  • Background in 3D perception, geometric representations, or learned representations relevant to physical interaction.
  • Experience with reinforcement learning in continuous control, model-based methods, or real-time policy execution.
  • A strong interest in building robust, real-world robotic systems, and motivation to see research ideas validated through physical experiments rather than simulation alone.
  • Track record of publications in top AI or robotics conferences (CoRL, ICRA, IROS, RSS, NeurIPS, CVPR, ICML).

Compensation:
The US base salary range for this full-time position is $38.00 - $46.00.
  • Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.
  • Please note that the compensation details listed in US role postings reflect the base salary only. It does not include discretionary bonus, equity, or benefits.

Apply