דרושים Phd Research Intern Computer Vision Deep Learning - ב-אנבידיה ב-ארהב

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

What we need to see:

• 10+ 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).

• 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.

• Proven success growing developer ecosystems through technical enablement.

What you'll be doing:

• Research, design and implement novel methods for efficient deep learning.

• Publish original research.

• Collaborate with other team members and teams.

• Mentor interns.

• Speak at conferences and events.

• Work with product groups to transfer technology.

• Collaborate with external researchers.

What we need to see:

• Completing or recently completed a Ph.D. in Computer Science/Engineering, Electrical Engineering, etc., or have equivalent research experience.

• Excellent knowledge of theory and practice of computer vision methods, as well as deep learning.

• Background in pruning, quantization, NAS, efficient backbones, and so on, is a plus.

• Experience with large language models and large vision-language models is required.

• Excellent programming skills in Python and PyTorch; C++ and parallel programming (e.g., CUDA) is a plus.

• Hands-on experience with large-scale model training including data preparation and model parallelization (tensor and pipeline) is required.

• Outstanding research track record.

• Excellent communications skills.

alignment, principledapproaches to synthetic data generation and filtering, advanced reasoning and inference algorithms for LLMs, novel learning paradigms and LLM architectures, and scientific understanding about the fundamental limitsand capabilitiesof LLMs. You will work within an amazing and collaborative research team that consistently publishes at the top venues in machine learning andnatural language

What you'll be doing:

• Explorealternative avenuesto unlock new capabilities in language models, including advanced knowledge acquisition techniques and innovative learning and decoding algorithms.

• Innovate newlearning paradigmsthat incorporate agency into the training of language models, such as enabling self-reflection and targeted knowledge enhancement.

• Enable learningfrom multi-modalitiesbeyond written text, such as acquiring physical commonsense knowledge through interactions with real-world environments.

• Publish original research.

• Collaborate with other team members and teams.

• Mentor interns.

• Speak at conferences and events.

• Work with product groups to transfer technology.

• Collaborate with external researchers.

What we need to see:

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

• At least 6 years of research experience (demonstrated by publication records spanning across 5+ years) in artificial intelligence, machine learning, natural language processing, computer vision or related subjects

• A history ofresearch successexemplified by a strong publication record and awards.

• Excellent knowledge of theory and practice of deep learning and natural language processing.

• Background in LLM training, alignment, and evaluation is expected.

• Excellent programming skills in Python and PyTorch.

• Hands-on experience with large-scale model training including data preparation and model parallelization (tensor and pipeline) is required.

• Excellent communications skills.

What you’ll be doing:

• Develop innovative parallel computing technologies that equip programmers with the compilers, languages, runtime systems, tools, and algorithms needed to solve challenges with modern accelerated systems.

• Collaborate with other researchers and engineers to extend the state of the art in parallel computing, machine learning, data analytics, and other technology areas surrounding NVIDIA's business. Deliver your innovations in high-quality software systems, publications, and patents.

• Engage with the research community through collaborations, publications, and presentations that produce new technologies and promote education in accelerated computing.

What we need to see:

• Completing or recently completed a Doctoral degree (Ph.D.) or equivalent experience in a computational field such as computer science, computer engineering, or scientific computing.

• Creativity in developing innovative solutions to the problems faced by parallel programmers and the skill to implement them in software.

• Expertise in parallel programming and algorithmic techniques.

• Strong programming ability in one or more of the following languages: C, C++, Rust and Python.

• Track record of research excellence and publications that demonstrate your body of work.

• Relevant research and software development experience.

Ways to stand out from the crowd:

• Expertise in applying programming system insights and techniques to problems in machine learning, data science, and distributed computing.

• Ability to implement ideas in the CUDA programming model.

• Experience with applying AI, such as large language models, to create new ways of solving the problems of software engineering.

• Prior success in building software systems used by other developers to solve their own problems.

In this critical role, you will manage a team to expand NeMo Framework's capabilities, enabling users to develop, train, and optimize models by designing and implementing the latest in distributed training algorithms, model parallel paradigms, model optimizations, defining robust APIs, meticulously analyzing and tuning performance, and expanding our toolkits and libraries to be more comprehensive and coherent. You will collaborate with internal partners, users, and members of the open source community to analyze, design, and implement highly optimized solutions.

What you’ll be doing:

• Plan, schedule, mentor, and lead the execution of projects and activities of the team.

• Collaborate with internal customers to align priorities across business units.

• Coordinate projects across different geographic locations.

• Grow and develop a world-class team.

• Contribute and advance open source

• Solve large-scale, end-to-end AI training challenges, spanning the full model lifecycle from initial orchestration, data pre-processing, running of model training and tuning, to model deployment.

• Work at the intersection ofcomputer-architecture,libraries, frameworks, AI applications and the entire software stack.

• Innovate and improve model architectures, distributed training algorithms, and model parallel paradigms.

What we need to see:

• Excellent understanding of SDLC practices including architecting, testing, continuous integration, and documentation

• MS, PhD or equivalent experience in Computer Science, AI, Applied Math, or related field

• 8+ overall years of industry experience, including 3+ years of management experience.

• Proven experience to lead and scale high-performing engineering teams, especially across distributed and functional groups.

• Experience with AI Frameworks (e.g. PyTorch, JAX), and/or inference and deployment environments (e.g. TRTLLM, vLLM, SGLang).

• Proficient in Python programming, software design, debugging, performance analysis, test design and documentation.

• Consistent record of working effectively across multiple engineering initiatives and improving AI libraries with new innovations.

Ways to stand out from the crowd:

• Hands-on experience in large-scale AI training, with a deep understanding of core compute system concepts (such as latency/throughput bottlenecks, pipelining, and multiprocessing) and demonstrated excellence in related performance analysis and tuning.

• Expertise in distributed computing, model parallelism, and mixed precision training.

• Prior experience with Generative AI techniques applied to LLM and Multi-Modal learning (Text, Image, and Video).

• Knowledge of GPU/CPU architecture and related numerical software.

• Created / contributed to open source deep learning frameworks.

What you'll be doing:

• Designing and implementing cutting-edge techniques in the field of vehicle autonomy.

• Publishing your original research.

• Collaborating with other research team members, a diverse set of internal product teams, and external researchers.

• Transferring technology you've developed to relevant product groups.

What we need to see:

• Completing or recently completed a PhD in Robotics, Computer Science, Computer Engineering or related field (or equivalent experience).

• Relevant research experience in the field of vehicle / robot autonomy.

• Strong knowledge of theory and practice of vehicle / robot autonomy, or a related area with a strong interest in connecting your work to autonomous vehicles.

• A track record of research excellence with your work published in top conferences and journals such as RSS, ICRA, IJRR, NeurIPS, ICML, CVPR, TAC, etc, and other research artifacts such as software projects.

• Exceptional programming skills in Python; C++ and parallel programming (e.g., CUDA) are a plus.

• Knowledge of common machine learning frameworks such as PyTorch and Tensorflow.

• Strong communication and interpersonal skills are required along with the ability to work in a dynamic, research-focused team.

What you will be doing:

• Design and build PyTorch components that run efficiently on supercomputers with 1000s-100ks of GPUs.

• Collaborate with NVIDIA’s hardware and software teams to improve the overall GPU performance in PyTorch.

• Design, build and support production AI solutions used by enterprise customers and partners.

• Work with internal applied researchers to improve their AI tools.

What we need to see:

• BS in Computer Science or Engineering (or equivalent experience).

• 3+ years professional experience in deep learning.

• Proficient with C++ programming.

• Strong understanding of systems software and interfaces.

• Demonstrated experience with Thread and Distributed Parallel Programming

• Demonstrated background developing large software projects.

• Strong verbal and written communication skills

Ways to stand out from the crowd:

• Contributions and participation in the open source community.

• Familiarity with deep learning compilers.

• Familiarity with deep learning modeling trends.

• Background with CUDA Programming as well as Python.

• Demonstrated experience working with multi-disciplinary teams.