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Python Robotics Jobs in Gilroy, CA (NOW HIRING)

Figure

Firmware Intern [Fall 2026]

San Jose, CA · On-site

$40 - $45/hr

Figure is an AI robotics company developing autonomous general-purpose humanoid robots. The goal of ... Develop Python tools to support test automation or hardware calibration * Contribute to the ...

Figure

Firmware Intern [Fall 2026]

San Jose, CA · On-site

$40 - $45/hr

Figure is an AI robotics company developing autonomous general-purpose humanoid robots. The goal of ... Develop Python tools to support test automation or hardware calibration * Contribute to the ...

Figure

Special Projects Intern [Fall 2026]

San Jose, CA · On-site

$40 - $45/hr

Strong software engineering skills, with proficiency in Python. * Experience applying AI or machine learning, ideally in a robotics context. * Working knowledge of robotics fundamentals, such as ...

Figure

Special Projects Intern [Fall 2026]

San Jose, CA · On-site

$40 - $45/hr

Strong software engineering skills, with proficiency in Python. * Experience applying AI or machine learning, ideally in a robotics context. * Working knowledge of robotics fundamentals, such as ...

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All JobsPython Robotics JobsPython Robotics Jobs in Gilroy, CA

Python Robotics information

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How much do python robotics jobs pay per hour?

As of Aug 7, 2026, the average hourly pay for python robotics in Gilroy, CA is $62.04, according to ZipRecruiter salary data. Most workers in this role earn between $51.15 and $70.48 per hour, depending on experience, location, and employer.

What is a Python Robotics job?

Python Robotics jobs involve designing, developing, and programming robotic systems using the Python programming language. Professionals in this field use Python to control robots, process sensor data, automate tasks, and integrate with hardware and software systems. These roles may be found in industries like manufacturing, healthcare, research, and autonomous vehicles. Typical responsibilities include writing code for robotic behavior, working with frameworks like ROS (Robot Operating System), and collaborating with engineers to build intelligent machines.

How do Python Robotics engineers typically collaborate with interdisciplinary teams during a project?

Python Robotics engineers often work closely with mechanical, electrical, and systems engineers to develop and integrate robotic solutions. They are responsible for writing and testing control algorithms in Python, as well as interfacing with hardware and simulation tools. Regular communication and joint problem-solving sessions are common, ensuring that software aligns with hardware capabilities and project requirements. This collaborative environment helps deliver robust, efficient robotic systems and offers exposure to various engineering domains.

What is the difference between Python Robotics vs Robotics Software Engineer?

AspectPython RoboticsRobotics Software Engineer
Required CredentialsPython programming skills, robotics knowledge, possibly certifications in Python or roboticsProficiency in robotics software, programming skills (Python, C++), engineering degree often preferred
Work EnvironmentResearch labs, robotics companies, startups, often hands-on with hardware and softwareDevelopment teams, engineering departments, focus on software development for robotic systems
Industry UsageUsed in robotics research, automation projects, and hobbyist communitiesApplied in industrial automation, autonomous vehicles, and advanced robotics projects

Python Robotics typically refers to using Python programming in robotics applications, often in research or hobbyist settings. Robotics Software Engineers focus on developing and maintaining complex software systems for robotic hardware in professional environments. While both roles require programming skills and robotics knowledge, Python Robotics emphasizes scripting and experimentation, whereas Robotics Software Engineers work on scalable, production-level software solutions.

What are the key skills and qualifications needed to thrive as a Python Robotics engineer?

To thrive as a Python Robotics Engineer, you need strong programming skills in Python, a solid understanding of robotics concepts, and often a degree in robotics, computer science, or engineering. Familiarity with robotics frameworks like ROS (Robot Operating System), simulation tools such as Gazebo, and experience with hardware integration are commonly required. Problem-solving, adaptability, and effective teamwork are essential soft skills that help address complex technical challenges and collaborate with interdisciplinary teams. These competencies enable the design, implementation, and optimization of robust robotic systems in a rapidly evolving field.
What are popular job titles related to Python Robotics jobs in Gilroy, CA? For Python Robotics jobs in Gilroy, CA, the most frequently searched job titles are:
What job categories do people searching Python Robotics jobs in Gilroy, CA look for? The top searched job categories for Python Robotics jobs in Gilroy, CA are:
What cities near Gilroy, CA are hiring for Python Robotics jobs? Cities near Gilroy, CA with the most Python Robotics job openings:
Python Robotics jobs near you

AI Robotics Researcher Intern (Dexterous Manipulation)

NIO

San Jose, CA

Full-time

Re-posted 23 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.
  • Generative Embodied 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.

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