Nvidia Internships Phd Robotics Research jobs at Nvidia

What you'll be doing:

• Develop new Deep Learning models for automatic speech recognition, speech synthesis, neural machine translation and natural language

• Design new large scale training algorithm

• Open-source models using NeMo conversational AI frameworks

• Mentor interns

• Publish research papers on top speech and NLP conferences

• Collaborate with universities and research teams.

What we need to see:

• PhD in Computer Science or Electrical Engineering (or equivalent experience)

• Proven understanding of Deep Learning for Natural Language Processing or Speech Recognition

• At least 5 years of research experience in speech recognition or NLP

• Excellent Python programming skills

• Experience with PyTorch

• Strong publications record

Ways to stand out from the crowd:

• Contribution to open-source projects

• Being reviewers for one of the top speech conferences

As a Research Scientist specializing in Generative AI for Physical AI, you'll be at the forefront of developing next-generation algorithms that bridge the gap between virtual and physical realms. You'll work with state-of-the-art technology and have access to massive computational resources to bring your ideas to life.

What you'll be doing:

• Pioneer revolutionary generative AI algorithms for physical AI applications, with a focus on advanced video generative models and video-language models

• Architect and implement sophisticated data processing pipelines that produce premium-quality training data for Generative AI and Physical AI systems

• Design and develop cutting-edge physics simulation algorithms that enhance Physical AI training

• Scale and optimize large-scale training systems to efficiently harness the power of 20,000+ GPUs for training foundation models

• Author influential research papers to share your groundbreaking discoveries with the global AI community

• Drive innovation through close collaboration with research teams, diverse internal product groups, and external researchers

• Build lasting impact by facilitating technology transfer and contributing to open-source initiatives

What we need to see:

• PhD in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience).

• Deep expertise in PyTorch and related libraries for Generative AI and Physical AI development

• Strong foundation indiffusion, vision language and reasoning models and their applications

• Proven experience with reinforcement learning algorithms and implementations

• Robust knowledge of physics simulation and its integration with AI systems

• Demonstrated proficiency in 3D generative models and their applications

Ways to stand out from the crowd:

• Publications or contributions to major AI conferences (ICLR, NeurIPS, ICML, CVPR, ECCV, SIGGRAPH, ICCV, etc.)

• Experience with large-scale distributed training systems

• Background in robotics or physical systems

• Open-source contributions to prominent AI projects

• History of successful research-to-product transitions

What you’ll be doing:

• Act as a technical advisor, collaborating with partner engineering teams on architecture, integration, and code for Isaac Sim, Isaac Lab, and AI-enabled robotics solutions.

• Build and maintain deep expertise in NVIDIA robotics SDKs, with a focus on simulation and robot learning.

• Track emerging trends in the robotics ecosystem to identify new opportunities.

• Co-design and deliver advanced robotic solutions with partners—defining objectives, architecture, milestones, and implementation plans.

• Create technical enablement resources, including sample code, reference architectures, integration guides, and workshops.

• Work closely with partner engineering leaders and decision-makers to identify challenges, recommend solutions, and drive adoption of NVIDIA robotic technology.

• Represent partner needs internally, providing feedback to NVIDIA’s product and engineering teams to influence future roadmaps.

• Support robotics startups with their synthetic data generation strategy.

• Support product launches and go-to-market activities with technical validation, demos, and customer-facing materials.

What we need to see:

• 6+ years in the technology industry, with at least 5 years in hands-on software development or engineering.

• Bachelor’s or Master’s in Computer Science, Engineering, or a related technical field—or equivalent experience.

• Whole software development lifecycle experience—from requirements and design to testing, integration, and support.

• Technical background in at least one of: robot foundation models, simulation, synthetic data, robot perception, reinforcement learning, or imitation learning.

• Expertise with robotics simulation tools (e.g., Gazebo, MuJoCo, Isaac Sim, Robot Studio).

• Fluency with NVIDIA Jetson compute platforms and the Jetpack SDK

• Experience leading technical workshops, code reviews, and architectural design sessions.

• Strong communication skills for technical and executive audiences.

• Ability to structure and deliver complex technical engagements.

Ways to stand out from the crowd:

• Experience with NVIDIA tools and libraries (CUDA-X, Isaac Sim, OpenUSD, Cosmos).

• Recent hands-on experience with robot simulation tools.

• Knowledge of AIOps, cloud-native technologies, Kubernetes, Docker, and monitoring tools.

• Experience in training computer vision and/or kinematic foundation models

• Proven success in growing developer ecosystems through technical enablement.

We, the

What you’ll be doing:

• Decompose research questions into smaller, more manageable parts and tackle them in iterative steps.

• Think critically to identify unseen gaps, and creatively bridge them with non-traditional, high-impact solutions.

• Connect with researchers and product engineers to ground research findings in real-world problems.

• Lead knowledge dissemination effort, with options for conference, journal, and in-house publication.

What we need to see:

• Currently pursuing a Ph.D. in the field of Computer Science/Engineering, Electrical Engineering, or related fields.

• Experience in gaming and/or human behavior in related application domains, demonstrated by one or more lead-author publications.

• Examples of public portfolios (e.g. repositories, OSS contributions, notebooks, packages, or technical blog posts with code).

• Proficiency with Python, Rust, and/or C++.

• Experience with AI model training and evaluation frameworks, like PyTorch.

• Comfortable with modern software development and version-control systems (e.g., GitHub/lab).

• Familiarity with and interest in modern deep learning models, including working with large-scale, multi-modal foundation models (such as recent LLMs, VLMs).

• Strong understanding of deep learning fundamentals and recent trends.

Ways to stand out from the crowd:

• Experience with multi-node, multi-GPU training and inference workflows.

• Proficiency in crafting, implementing, and conducting behavioral experiments involving human subjects and interactive visual stimuli.

• Experience with quantitatively modeling human perception, movement, and decision-making.

• A track record of applying human behavior models to machine learning applications.

You will also be eligible for Intern

As a Software Engineer in Robotics at NVIDIA, you will play a key role in advancing the field of robotics by working on state-of-the-art technology and infrastructure. You will be part of a dedicated team focused on developing and deploying robotics systems that blend both simulation and real-world applications. If you are enthusiastic about building infrastructure that removes friction and directly enables a team's ability to iterate rapidly, while gaining exposure to the complex challenges of production-grade robotic software, this position is right for you.

What You'll Be Doing:

• Drive exceptional developer experience and rapid iteration speed by targeting friction points in existing processes and delivering the vital technical infrastructure to ensure smooth, fast workflows.

• Improve build systems, speed up CI pipelines, and streamline training workflows.

• Demonstrate your understanding of the unique challenges in the robotics ecosystem to propose solutions that accelerate robot learning.

• Integrate hardware-in-the-loop (HIL) testing into CI to verify robotics systems under real-world conditions.

• Collaborate across team boundaries to identify the biggest challenges and the best solutions.

What We Need to See:

• Master's degree in Computer Science, Engineering, or a related field (or equivalent experience).

• 8+ years of robotics software and build systems experience.

• A strong, intrinsic drive to passionately pursue and eliminate development friction, bottlenecks, and toil.

• Expertise in Bazel and CMake for codebases consisting mainly of C++ and Python.

• Hands-on experience building reliable and scalable CI/CD pipelines (GitLab, GitHub).

• Experience with automation of physical systems, such as Hardware-In-the-Loop test setups.

• Proficient at resolving intricate issues when faced with uncertainty.

• Excellent communication skills and a collaborative approach to working effectively with diverse teams.

Ways to Stand Out from the Crowd:

• Practical experience with tools used in the NVIDIA robotics ecosystem such as Jetson, Isaac Sim, Warp, and CUDA.

• Familiarity with advanced robotics concepts and real-world deployment challenges.

• Experience with remote caching and execution with Bazel.

• Demonstrated success in deploying intricate robotics systems across diverse settings.

What you'll be doing:

• Leading the end-to-end product lifecycle, from new features to supporting new AI platforms, delivering multiple releases per year.

• Collaborating with cross-functional teams, including engineering, marketing, and sales, to successfully implement product strategies and roadmaps.

• Writing clear requirements, user stories, and compelling user experiences to ensure a quality product.

• Managing release schedules and coordinating with development teams to ensure timely delivery of enterprise software products.

• Applying sophisticated product management software to monitor progress, track metrics, and report on the success of product initiatives.

What we need to see:

• Bachelor's degree in Computer Science, Engineering, or equivalent experience.

• Minimum of 8 years of experience in software product management.

• Extensive hands-on experience with compute, network, and storage technologies.

• Proven proficiency in release management strategies and adept utilization of product management software tools.

• Proven written and verbal communication skills. Ability to effectively connect with technical and non-technical stakeholders.

• Leadership skills! Remove obstacles. Resolve ambiguity. Comfortable presenting and defending your fact-based opinion or recommendation.

Ways to stand out from the crowd:

• Hands-on experience with NVIDIA Base Command Manager or Bright Cluster Manager

• Experience as an SRE, datacenter operator, infrastructure manager

• Experience with high-performance computing

• Background with Software Development Life Cycle

We, the

What you’ll be doing:

• Decompose research questions into smaller, more manageable parts and tackle them in iterative steps.

• Think critically to identify unseen gaps, and creatively bridge them with non-traditional, high-impact solutions.

• Connect with researchers and product engineers to ground research findings in real-world problems.

• Lead knowledge dissemination effort, with options for conference, journal, and in-house publication.

What we need to see:

• Currently pursuing a Ph.D. in the field of Cognitive Science, Neuroscience, Computer Science/Engineering, Electrical Engineering, or related fields..

• Experience in cross-disciplinary research that applies knowledge from human vision to drive innovations in AI and computer vision, demonstrated by one or more lead-author publications.

• Proficiency with Python.

• Experience with AI model training and evaluation framework PyTorch or similar.

• Comfortable with modern software development, version-control systems, like git(hub/lab).

• Familiarity with and interest in modern deep learning models, including working with large-scale, multi-modal foundation models (such as recent LLMs, VLMs).

• Strong understanding of deep learning fundamentals and recent trends.

Ways to stand out from the crowd:

• Prior work applying human vision science to machine learning and computer vision.

• Proficient in crafting, implementing, and conducting behavioral experiments involving human subjects and interactive visual stimuli.

• Experience with quantitatively modeling human perception, cognition, movement, and/or decision-making.

• Background with multi-node, multi-GPU training and inference workflows.

You will also be eligible for Intern