Full-Time

Senior Research Engineer

Robotics Systems

Confirmed live in the last 24 hours

NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI computing solutions

Automotive & Transportation
Enterprise Software
AI & Machine Learning
Gaming

Compensation Overview

$224k - $356.5kAnnually

+ Equity

Expert

Company Historically Provides H1B Sponsorship

Santa Clara, CA, USA

Physically work on-site at NVIDIA HQ on all business days.

Category
Robotics and Automation Engineering
Mechanical Engineering
Required Skills
Rust
Python
Neural Networks
C/C++

You match the following NVIDIA's candidate preferences

Employers are more likely to interview you if you match these preferences:

Degree
Experience
Requirements
  • A Bachelor’s Degree in Computer Science, Robotics, Engineering, or a related field
  • 10+ years of full-time industry experience in robotics hardware or software full-stack
  • Hands-on experience with deploying and debugging neural network models on robotic hardware
  • Ability to implement real-time control algorithms, teleoperation stack, and sensor fusion
  • Proficiency in languages such as Python, Rust, C++, and experience with robotics frames (ROS) and physics simulation (Gazebo, Mujoco, Isaac, etc.)
  • Experience in maintaining and troubleshooting robotic systems, including mechanical, electrical, and software components
  • Physically work on-site at NVIDIA HQ on all business days
Responsibilities
  • Design and maintain teleoperation software for controlling humanoid robots with low latency and high precision
  • Develop and optimize the control stack, including locomotion, manipulation, and whole-body control algorithms
  • Deploy and evaluate neural network models in physics simulation and on real humanoid hardware
  • Implement tools and processes for regular robot maintenance, diagnostics, and troubleshooting to ensure system reliability
  • Monitor teleoperators at the lab and develop quality assurance workflows to ensure high-quality data collection
  • Collaborate with researchers on model training, data processing, and the full MLOps lifecycle
Desired Qualifications
  • Master’s or PhD’s degree in Computer Science, Robotics, Engineering, or a related field
  • Experience at autonomous driving or humanoid robotics companies on real hardware deployment
  • Experience in robot hardware design
  • Demonstrated Tech Lead experience, coordinating a team of robotics engineers and driving projects from conception to deployment
  • Contributions to popular open-source robotics frameworks or research publications in top-tier conferences, such as ICRA, IROS, RSS, CoRL

NVIDIA designs and manufactures graphics processing units (GPUs) and system on a chip units (SoCs) for various markets, including gaming, professional visualization, data centers, and automotive. Their products include GPUs tailored for gaming and professional use, as well as platforms for artificial intelligence (AI) and high-performance computing (HPC) that cater to developers, data scientists, and IT administrators. NVIDIA generates revenue through hardware sales, software licenses, and cloud-based services, such as NVIDIA CloudXR and NGC, which enhance applications in AI, machine learning, and computer vision. Unlike many competitors, NVIDIA focuses heavily on research and development to maintain its leadership in technology and innovation. The company's goal is to drive advancements in AI and computing to provide effective solutions for a wide range of clients, from gamers to enterprises.

Company Stage

IPO

Total Funding

$19.5M

Headquarters

Santa Clara, California

Founded

1993

Growth & Insights
Headcount

6 month growth

0%

1 year growth

0%

2 year growth

-1%
Simplify Jobs

Simplify's Take

What believers are saying

  • Acquisition of VinBrain enhances NVIDIA's AI-driven healthcare solutions.
  • Investment in Nebius Group boosts NVIDIA's AI infrastructure capabilities.
  • Partnership with Serve Robotics aligns with NVIDIA's focus on robotics and AI applications.

What critics are saying

  • Increased competition from AI startups like xAI challenges NVIDIA's market position.
  • Serve Robotics' rapid expansion may lead to financial strain if market growth lags.
  • Integration challenges from VinBrain acquisition may affect NVIDIA's operational efficiency.

What makes NVIDIA unique

  • NVIDIA leads in AI and HPC solutions with cutting-edge GPU technology.
  • The Omniverse platform enhances NVIDIA's capabilities in industrial AI and digital twins.
  • NVIDIA's cloud services, like CloudXR, offer scalable solutions for AI and machine learning.

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Benefits

Company Equity

401(k) Company Match