NVIDIA

Artificial Intelligence

• Plan and build complex cluster and supercomputers in various of data center and labs
• Rack stack and cable management to ensure efficient use of space and easy maintenance
• Ensure data centers and labs power and cooling efficiency while optimizing rack space utilization
• Data centers and labs daily operation and support
• Installations for variety of infrastructure and solutions - Cloud, VMs, Storage, Network, HPC and AI
• Perform troubleshooting - network, optic cabling, bare metal, operating system
• Support Research & Development activities

HPC and AI Data Center Engineer

Solutions Engineer

• You will partner with our business / account team working with customers to develop a keen understanding of their goals, strategies, and technical needs as well as help to define and deliver high-value solutions meeting these needs.
• Staying up on the state of the art in the production deep learning and machine learning methods.
• You'll be called on to help architect and scale high-performance, distributed, AI deployments that are built on the latest NVIDIA GPU supercomputers.
• Document what you know and teach others.
• Be an industry leader with vision on integrating NVIDIA technology into AI and HPC architectures for advanced applications, such as foundation model training or autonomous labs.
• Strategically partner with lighthouse customers and industry-specific solution partners targeting our computing platform.

Solutions Architect – Deep Learning for Drug Discovery

Full-stack Engineer

• Develop innovative SW solutions
• Take part in defining methodologies affecting design and verification engineers day to day work
• Improve existing tools, which are used in-house by electrical engineers for designing the next generation leading AI chips, SoCs and Switches.
• Collaborate with designers, verification specialists and architects to accomplish your tasks

Senior Software Engineer, Chip Design

Engineer

• Research and development of techniques to accelerate applications in computational engineering (CAE, CFD, EDA), high performance computing, scientific computing, data analytics, and artificial intelligence.
• Perform in-depth analysis and optimization to ensure best performance on CPU, GPU, and network architectures.
• Engage with experts to understand and address their problems.
• Guide key application developers and contribute directly to applications.
• Develop reference codes or libraries.
• Optimize core parallel algorithms and data structures using NVIDIA platform.
• Collaborate with diverse groups like architecture, research, libraries, tools, system software, and product management teams.

Compute DevTech Engineer

• Design, develop, and maintain high-performance libraries and APIs in C++ and Python for accelerated and distributed quantum–HPC computing
• Lead the productization of new functionality end to end, including design, implementation, debugging, testing, performance optimization, and documentation
• Prototype and evaluate innovative algorithms and proof-of-concept implementations, transitioning successful ideas into production-quality software
• Drive opportunities to improve library quality, performance, scalability, and maintainability through thoughtful re-architecture and modern software engineering practices
• Collaborate closely with product management, architects, and internal and external partners to understand user workflows, define requirements, and contribute to technical roadmaps
• Communicate technical designs, results, and guidelines effectively across teams, and represent the work through internal reviews, documentation, or technical forums as appropriate

Senior Quantum Software Engineer

Designer

• Develop and support component libraries for advanced process technologies
• This will involve developing and maintaining technology files, symbols, gates and pcells, and supporting various netlisters
• Install, configure and support foundry PDKs
• Maintain the custom design environment used by custom schematic and mask designers
• Write scripts using Perl, Python, and Cadence SKILL
• Support and maintain CAD tools used by IC designers including Virtuoso, IC-Manage, HSPICE, ADE, various simulation tools and Verilog / System Verilog
• Work with CAD tool vendors to evaluate new tools, solve bugs, improve usability, etc.
• Develop infrastructure to support design work in new process technologies

Senior Custom CAD Engineer – Custom Circuit Designers

• Help building high-fidelity 3D scene representations from sparse or multi-view data.
• Collaborate closely with research and development teams to design, train, and deploy advanced neural reconstruction models.
• Develop models that capture geometry, appearance, and semantics, to generate 3D scenes and integrate them into production systems and tools.
• Help push the boundaries of neural reconstruction technology and tackle intellectually demanding, highly impactful challenges.

Senior System Software Engineer, 3D Computer Vision

• Improve coverage of the RAPIDS Spark plugin to enable more operators and execs from Apache Spark to be GPU accelerated
• Enable fast I/O on table layout formats like Delta and Apache Iceberg
• Profile code to identify and implement performance improvements
• Work on native code (C++) implementations of Apache Spark functionality
• Work with open source communities to enhance RAPIDS through technical discussion and code contributions

Senior System Software Engineer

Hardware Engineer

• Working on bringing up next-generation NIC devices
• Collaborating closely with Chip Design, Firmware, and Software teams during integration activities
• Supporting NIC Firmware code for new devices
• Preparing regression for NIC models on emulation environments
• Improving the team’s work efficiency by adapting methodologies and automating routine activities

Senior Firmware Engineer

• Collaborate with NVIDIA Cloud Partners to create, implement, and deliver on NVIDIA's innovative hardware and software solutions
• Partner with SAs, Account Managers, Engineering, Product, and business leaders to align on strategies, assess technical needs, secure business opportunities for NVIDIA
• Become the primary technical driver for customers during the design, development, construction, integration, and production of GPU Cloud infrastructure and applications throughout the entire customer lifecycle
• Conduct regular technical customer meetings for project/product details, feature discussions, intro to new technologies, and debugging sessions
• Work closely with customers to build and adopt NVIDIA solutions including PoCs to address critical business needs covering infrastructure, libraries, and applications
• Prepare and deliver technical content to customers including presentations, workshops, reference architectures, tutorials, publications.

Senior Solutions Architect, Cloud Partners

Systems Engineer

• Direct and drive key initiatives vital to complete several projects within the AV Fleet.
• These initiatives range from driving org level optimizations to scaling out AV testing.
• Analyze & diagnose the underlying events contributing to these metrics, identify trends, and resolve top priority engineering work for improving the platform experience.
• Drive implementation and/or recommend improvements across features and across the stack, in collaboration with the corresponding component engineering teams.
• Scale out this iterative development process by developing more automation and leveraging from current operational teams/resources.
• Assist in improving process and procedures within the team.
• Help streamline day-to-day operations.

Senior Technical Program Manager, System Integration and Test – Autonomous Vehicles

Research Scientist

• Develop new deep learning-based approaches to improve capabilities of large AI Models.
• Design and implement techniques for post training such as model alignment.
• Transfer your research to NVIDIA’s software product teams.
• Publish your research at conferences such as EMNLP, ACL, ICLR, ICML, NeurIPS, etc.
• Partner with AI researchers in leading universities and industrial research labs.
• Open source your models and algorithms as part of NVIDIA NeMo.

Applied Scientist – AI Enterprise Products

• verify the design and implementation of our state of the art memory subsystem for our mobile SoCs and GPUs
• responsible for verification of memory subsystem or coherent high speed interconnect design, architecture, golden models and micro-architecture using advanced verification methodologies
• understand the design & implementation, define the verification scope, develop the verification infrastructure (Testbenches, BFMs, Checkers, Monitors), execute test/coverage plans, and verify the correctness of the design
• Collaborate with architects, designers, emulation and silicon verification teams to accomplish your tasks

Verification Engineer, New College Grad

Developer Relations

• 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.

Robotics Developer Relations Manager

• Design and implement the DSL and the core compiler of tile-aware GPU programming model for emerging GPU architectures
• Continuously innovate and iterate on the core architecture of the compiler to consistently optimize performance
• Investigation of next-generation GPU architectures and provide solutions in the DSL and compiler stack
• Performance analysis on emerging AI/LLM workloads and integrate with AI/ML frameworks