Nvidia Internships Phd Graphics Simulation 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:

• Architect, build, plan, implement, and operate cloud services relating to video technologies

• Collaborate and integrate system and runtime integration problems across the Vulkan/Proton team and video streaming teams.

• Work with game and application developers and our internal platform/performance teams for optimizations in Unreal

• Maintain a customer-centric approach by supporting, maintaining, and detailing software functionality.

What we need to see:

• BS/MS in Computer Science or equivalent experience with 15+ years of hands-on experience building complex services.

• Expertise in Go and working with cloud services. Have designed and implemented high-scale, reliable systems.

• Deep understanding of HTTP REST API, gRPC, security, and networking, along with a good grasp of API development influenced by UX/UI/CLI requirements.

• Ability to drive pragmatic technical discussions towards practical solutions that are clean, reusable, testable, and extensible.

• Dedication to collaborative development approaches, with the capability to impact daily operations across teams and collaborators.

• Strong debugging skills to pinpoint underlying issues and enhance the technology stack, working closely with colleagues and team members like DevSecOps and SRE or those with equivalent experience.

• Strong verbal and written communication abilities, with a demonstrated history of being a standout colleague.

Ways to stand out from the crowd:

• Experience in the game industry with Unreal Engine

• Expertise in Java, Spring Boot, Golang, Gatling, Python, Kubernetes, and Docker.

• Familiarity with NoSQL databases such as Cassandra, DynamoDB, and Redis.

• Ability to excel in a dynamic, highly interactive environment, driving team success.

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

What you’ll be doing:

• Operate as a technical advisor and problem solver with partner engineering teams, collaborating on architecture, code, and integration for Omniverse and AI-enabled solutions.

• Actively prototyping to develop deep expertise in NVIDIA Cosmos, Omniverse Platforms, NuRec and related technologies (APIs, USD, NIMs, Blueprints) through hands-on technical integration.

• Implement intricate technical solutions with partners—defining objectives, architecture, landmarks, and delivery plans while contributing code samples, architecture diagrams, and hands-on engineering support.

• Provide technical enablement resources like workshops, reference architectures, and integration guides to speed up adoption and standard processes while collaborating with engineering and leadership teams across partner organizations to identify goals, resolve technical challenges, and align on architecture and solution direction.

• Advocate for partner technical needs within NVIDIA—providing actionable feedback to influence product roadmaps and future technology direction while supporting product launches and go-to-market activities, ensuring seamless integration and technical excellence in customer-facing materials.

• Guide research and implementation in 3D reconstruction, integrating innovations like Gaussian splatting into autonomous simulation pipelines.

What we need to see:

• Master’s or Ph.D. in Computer Science, Electrical/Computer Engineering, Artificial Intelligence, or a related field (or equivalent experience).

• 8+ years of hands-on experience in a technical AI role, with emphasis on autonomous systems, simulation, or generative AI.

• Programming expertise in Python and C++, with solid software design and debugging experience on Linux with a deep understanding of Autonomous Vehicle systems, including sensors, dynamics, perception, prediction, planning, and control.

• Hands-on experience with DevOps tools (GitLab, Docker, Kubernetes) and scalable distributed systems and Deep Learning (DL) and Reinforcement Learning (RL) frameworks experience such as PyTorch or JAX.

• Expertise in computer vision and 3D reconstruction technologies.

• Excellent communication, collaboration, and presentation skills with the ability to engage technical and non-technical audiences.

• Highly motivated and passionate about driving technical innovation and sharing knowledge!

Ways to stand out from the crowd:

• Hands-on experience with LiDAR, radar, camera, IMU, and other sensor modalities.

• Familiarity with NVIDIA Cosmos, NuRec, Isaac Sim, Isaac Lab, and Omniverse for physical AI simulation and synthetic data generation.

• Strong GPU optimization and profiling expertise using Nsight Systems and Nsight Compute.

• CUDA programming experience, model quantization, and inference acceleration.

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