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Robotics Researcher Jobs (NOW HIRING)

Team Red Dog

AI Robotics Engineer

Redmond, WA · On-site

Working alongside leading researchers, you'll help advance open-source robotics software, improve model performance, and contribute to technologies shaping the next generation of intelligent ...

Team Red Dog

AI Robotics Engineer

Redmond, WA · On-site

Working alongside leading researchers, you'll help advance open-source robotics software, improve model performance, and contribute to technologies shaping the next generation of intelligent ...

Aramco

Robotics Research Engineer

Houston, TX · On-site

Aramco Americas Company Robotics Research Engineer - Software (1830) R&D Digital Transformation Team Staff - Houston, TX - Full Time OVERVIEW: The Sensors and Robotics Team at Aramco's Houston ...

Nimble

AI Robotics Research Engineer

San Francisco, CA · On-site

They are seeking an AI Robotics Research Engineer to design, develop, and implement robotic foundation models and reinforcement learning algorithms for multi-agent robot fleets. Responsibilities ...

Nimble

AI Robotics Research Engineer

San Francisco, CA · On-site

The AI Robotics Research Engineer will design, develop, train, and implement robotic foundation models and reinforcement learning algorithms for multi-agent robot fleets. Responsibilities : • ...

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All JobsRobotics Researcher Jobs

Robotics Researcher information

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$30K

$113.1K

$164.5K

How much do robotics researcher jobs pay per year?

As of Aug 6, 2026, the average yearly pay for robotics researcher in the United States is $113,102.00, according to ZipRecruiter salary data. Most workers in this role earn between $67,000.00 and $154,000.00 per year, depending on experience, location, and employer.

What is a robotics researcher?

Robotics Researchers are professionals who study, design, and develop robots and robotic systems. They work on advancing the technology behind robots, exploring areas such as artificial intelligence, machine learning, computer vision, sensors, and mechanical design. Their goal is to improve how robots perceive, interact with, and respond to their environment, enabling robots to perform tasks in industries like manufacturing, healthcare, and space exploration. Robotics Researchers typically work in academic, corporate, or government research labs, collaborating with engineers and scientists from various fields.

What is the difference between Robotics Researcher vs Robotics Engineer?

AspectRobotics ResearcherRobotics Engineer
CredentialsAdvanced degrees (Master's/Ph.D.) often requiredBachelor's or Master's degree in engineering or related field
Work EnvironmentResearch labs, universities, R&D departmentsIndustrial settings, manufacturing, product development
Primary FocusDeveloping new algorithms, theories, and prototypesDesigning, building, and testing robotic systems
Employer & Industry UsageAcademic institutions, research organizations, tech companiesManufacturers, tech firms, automation companies

While both roles involve robotics, a Robotics Researcher primarily focuses on advancing knowledge through research and innovation, often in academic or R&D settings. In contrast, a Robotics Engineer applies existing knowledge to develop practical robotic systems and solutions in industry.

What are some common challenges robotics researchers face when transitioning their work from simulation to real-world implementation?

A common challenge for Robotics Researchers is ensuring that algorithms and systems developed in simulation perform reliably on physical robots. Real-world environments introduce unpredictable variables such as sensor noise, hardware limitations, and dynamic obstacles that are often simplified or absent in simulations. Researchers must frequently iterate on their designs, conduct extensive testing, and collaborate with hardware engineers to bridge this gap. Adapting to these challenges requires flexibility, attention to detail, and strong problem-solving skills.

What are the key skills and qualifications needed to thrive as a robotics researcher?

To thrive as a Robotics Researcher, you need a strong background in robotics, computer science, engineering, and mathematics, usually supported by a relevant advanced degree (Master's or PhD). Proficiency in programming languages (such as Python, C++), simulation tools (like ROS, Gazebo), and machine learning frameworks is typically required. Creativity, problem-solving, and effective collaboration are essential soft skills that set successful researchers apart. These skills and qualities are crucial for driving innovation, overcoming technical challenges, and advancing the field of robotics.
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What cities are hiring for Robotics Researcher jobs? Cities with the most Robotics Researcher job openings:
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Robotics Researcher jobs near you
Infographic showing various Robotics Researcher job openings in the United States as of August 2026, with employment types broken down into 90% Full Time, 5% Part Time, 4% Contract, and 1% Nights. Highlights an 93% Physical, 1% Hybrid, and 6% Remote job distribution, with an average salary of $113,102 per year, or $54.4 per hour.

AI Robotics Researcher Intern (Dexterous Manipulation)

NIO

San Jose, CA • On-site

Full-time

This job post has expired today. Applications are no longer accepted.

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.

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