Full-Time

Research Scientist – New College Grad 2025

Generalist Embodied Agent Research

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

$160k - $287.5kAnnually

+ Equity

Entry

Santa Clara, CA, USA

Remote option available, but requires in-office presence in Santa Clara.

Category
Robotics & Autonomous Systems
AI & Machine Learning
Required Skills
Python
Tensorflow
CUDA
Pytorch
C/C++
Requirements
  • Ph.D. in Computer Science/Engineering, Electrical Engineering, etc., or equivalent research experience.
  • Outstanding engineering skills in rapid prototyping and model training frameworks (PyTorch, Jax, Tensorflow, etc.). Python or C++ is required; CUDA or ROS proficiencies are a plus;
  • Excellent knowledge and hands-on experience for training LLMs, multimodal foundation models, or large generative models.
  • Experience in foundation and diffusion models, reinforcement learning, agent learning, and applied robotics
  • Experience across one or both of these fields: Multimodal Foundation Models
  • Hands-on training experience and publications in at least one of the following topics: LLMs; Large vision-language models; Video generative models and diffusion algorithms; Action-based transformers.
  • Excellent skills in working with large-scale machine learning/AI systems and compute infrastructure.
  • Robotics
  • Hands-on training experience and publications in robot learning, such as reinforcement learning, imitation learning, classical control methods, etc.
  • Deep understanding of robot kinematics, dynamics, and sensors;
  • Ability to safely operate robot hardware, lab equipment, and tools;
  • Knowledge of control methods, including PID, model predictive control, and whole-body control;
  • Familiarity with physics simulation frameworks such as MuJoCo and Isaac Sim;
  • Robot hardware design and hands-on building experience.
Responsibilities
  • Design and implement novel AI algorithms and models for general-purpose humanoid robots and embodied agents;
  • Develop large-scale AI training and inference methods for foundation models;
  • Optimize and deploy AI models in physical simulation and on robot hardware;
  • Collaborate with research and engineering teams across all of NVIDIA to transfer research to products and services.

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, such as GPUs, are essential for high-performance computing and artificial intelligence applications. NVIDIA's GPUs work by processing large amounts of data simultaneously, making them ideal for tasks like gaming graphics and complex computations in AI and machine learning. Unlike many competitors, NVIDIA focuses on both hardware and software solutions, offering cloud-based services that enhance the capabilities of their products. The company's goal is to drive innovation in AI and HPC, providing advanced solutions that cater to a wide range of clients, from gamers to researchers and enterprises.

Company Stage

IPO

Total Funding

$19.5M

Headquarters

Santa Clara, California

Founded

1993

Growth & Insights
Headcount

6 month growth

13%

1 year growth

25%

2 year growth

42%
Simplify Jobs

Simplify's Take

What believers are saying

  • NVIDIA's diverse investment portfolio offers employees exposure to cutting-edge technologies and industries, fostering a dynamic and innovative work environment.
  • The company's strategic acquisitions and partnerships provide opportunities for professional growth and cross-industry collaboration.
  • NVIDIA's strong financial backing and market leadership ensure stability and resources for continued innovation and development.

What critics are saying

  • NVIDIA's expansion into various sectors may dilute its focus and resources, potentially impacting its core GPU business.
  • The competitive landscape in AI, robotics, and autonomous vehicles is intense, posing challenges for NVIDIA to maintain its leadership position.

What makes NVIDIA unique

  • NVIDIA's strategic investments in diverse sectors like robotics, AI disease modeling, and driverless trucks highlight its commitment to pioneering technologies beyond its core GPU business.
  • The acquisition of Shoreline.io, a software startup, indicates NVIDIA's focus on enhancing its software capabilities, setting it apart from competitors primarily focused on hardware.
  • NVIDIA's involvement in significant funding rounds for companies like Mistral AI and Bright Machines showcases its influence and leadership in the AI and intelligent manufacturing sectors.

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