דרושים Nvidia Internships Phd Autonomous Vehicles Research ב-אנבידיה ב-ארהב

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

What you'll be doing:

• Lead, build, and drive the architecture and engineering alignment for key automotive customer projects through all phases, from bringup to production and post-production, using the DRIVE platform.

• Architect and build a seamless integration environment to amplify the scalability of our software solutions for our partners.

• Collaborate with senior leaders across the company to evolve the product initiatives, roadmaps, and processes. Drive innovation bringing in new technologies.

• Lead bring-up activities and provide deep technical guidance and strategies to resolve functional and system performance issues, working with internal and external partner teams.

• Collaborate with our global engineering teams in our US, APAC, and Europe locations to deploy the solution to our customers.

What we need to see:

• BE/BS or MS in computer science, robotics, computer engineering, or equivalent experience.

• Understand the technological evolution in the self driving industry.

• 15+ years of deep hands-on technical experience.

• Extensive strong technical leadership experience across large-scale organizations.

• Established proficiency in application development and scalability for autonomous machines, and familiarity with robotics or automotive related middleware frameworks.

• Broad and deep technical knowledge across software and hardware.

• Proven ability to lead teams across multiple hardware, software and business groups through design and implementation.

• Excellent communication and interpersonal skills and the ability to influence large organizations in meaningful ways.

Ways to stand out from the crowd

• Familiar with automotive design processes and norms (e.g. ISO 26262, ASPICE), including in-vehicle testing, simulation and metrics development of autonomous driving systems.

• Software development experience on QNX or equivalent RTOS.

• Applied knowledge in resolving sophisticated, interrelated issues emanating from sensors to other embedded controllers on the vehicle and from interactions between applications.

• Knowledge of GPU programming such as OpenCL or CUDA and understanding of the NVIDIA DRIVE platform.

• Contributions to or ownership of open-source project and mentorship experience.

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:

• Design and implement triggering systems and deploy containerized orchestration pipelines for distributed map creation, maintenance, and evaluation from crowdsourced vehicle data

• Develop map quality detection systems including automated hotspot detection algorithms and human-in-the-loop review workflows for large scale map validation

• Develop Python, C++, and JavaScript tools for map management, data validation, on-vehicle testing, and web-based geospatial visualizations

• Build C++ modules for on-vehicle map integration with perception, localization, and other consumers to ensure end-to-end validation of the maps' impact on driving performance

• Work with embedded systems and real-time constraints to optimize map consumption by autonomous driving software

• Collaborate with perception, planning, and operations teams to improve map quality and real-time driving performance

What we need to see:

• BS or MS degree in Computer Science, Software Engineering, or related field (or equivalent experience)

• 5+ years of proven experience building production data pipelines, distributed systems, mapping infrastructure, or map to vehicle integration

• Strong C++ programming skills for performance-critical algorithms, data processing tools, and on-vehicle software

• Strong Python programming skills for automation, workflow orchestration, and API development

• Proficiency with JavaScript for building web-based tools, visualizations, and internal dashboards

• Hands-on experience with Airflow or similar workflow orchestration frameworks

• Experience with Docker, Kubernetes, and cloud platforms

• Experience with Protocol Buffers, gRPC, and REST API design

• Excellent problem-solving skills and ability to debug sophisticated distributed and embedded systems

Ways to stand out from the crowd:

• Extensive experience with SD & HD mapping and autonomous vehicle software architectures

• Deep understanding of how maps are consumed by localization, perception, and planning systems in autonomous vehicles

• Deep knowledge of road topology generation, analysis, and graph partitioning algorithms

• Background with computer vision concepts pipelines (3D geometry, point clouds,structure-from-motion,COLMAP, SfM, visual odometry)

• Experience debugging and profiling performance on embedded platforms (NVIDIA Orin, Xavier, etc.)

What you will be doing:

• Develop, evaluate, and build architectures for Level 2 to Level 4 self-driving driver support and self-driving vehicle technologies

• Characterize autonomous vehicle interactions relative to vehicle requirements to drive data collection for system training and verification

• Drive autonomous vehicle system verification activities, including architecture and design verification, test strategy development working with the System Integration & Verification Test Leads, and reviewing and prioritizing test results

• Lead and communicate data analysis, working with product and engineering teams to drive design decisions relative to requirements and system behavioral needs

• Develop methods to analyze and compare the impact of ODDs on relevant performance metrics, translating data and analysis into impactful recommendations

What we need to see:

• BS, MS, or PhD in Mechanical Engineering, Electrical Engineering, Aerospace Engineering, Physics, Computer Science, or another related field, or equivalent experience.

• 5+ years of proven industry experience

• Strong analytics and architectural background in a development and production setting

• Experience in systems engineering, robotics development, or systems integration and test

• Strong leadership and interpersonal skills, with the ability to drive alignment between product development, engineering, and test teams.

Ways to stand out from the crowd:

• Experience with complex hardware and software systems

• Experience with software and/or tool development with a focus on modelling, analysis, utility languages such as Python. Success applying the systems V-Model to sophisticated engineering projects, ideally advanced driver assistance or autonomous vehicle systems and associated standards (e.g. ISO 26262)

• Deep technical background in at least one focus area of robotic systems development (e.g. sensing, perception, motion control)

• Experience with Model-Based Systems Engineering methods and tools, especially with Magic Cyber Systems Engineer / Cameo

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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:

• 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