NVIDIA

Operations

• Manage lab hardware inventory, including enterprise servers, prototype platforms, chips, fixtures, cables, peripherals, spare parts, and test equipment.
• Receive, label, rack, configure, deploy, maintain, and decommission hardware for engineering teams.
• Troubleshoot hardware, firmware, system bring-up, part swaps, repair coordination, and RMA workflows for benchtop and in-rack systems.
• Track hardware ownership, location, configuration, status, usage, lifecycle stage, and retirement readiness.
• Improve lab processes for check-in/check-out, deployment requests, repairs, safety, asset hygiene, and equipment readiness.
• Use AI tooling to automate and optimize daily operations rapidly and systematically.

R&D Lab Operations Manager

Blockchain Engineer

• Designing and developing a massively distributed scalable platform used to identify, diagnose and remediate non-performant GPU assets
• Working with teams across NVIDIA to ensure production AI clusters run reliably and consistently with maximum performance
• Evaluating system failures and improving services based on a well-defined incident management process
• Be part of a DGX Cloud team responsible for production systems that enable large scalable GPU clusters to be used for a variety of AI workloads

Senior Software Engineer – Distributed Systems

Production Engineer

• Leading a team of software and production engineers
• Driving execution in cluster operations, Kubernetes operability, automation
• Defining team priorities, roadmap, staffing, and operational ownership
• Partnering with platform, storage, security, and TPM teams
• Mentoring engineers, growing technical leaders

Engineering Manager – DGX Cloud Production Engineering

Cloud Engineer

• Build org-wide reliability strategy, guiding how NVIDIA matures its operational practices in a 24/7 environment
• Stand up a rigorous SLO program, defining and maintaining high standards across teams
• Lead incident response for high severity incidents, ensuring low drama and high signal resolution
• Build and improve production code daily, enhancing our data platform and related tooling
• Implement chaos engineering, failure injection, and resilience testing to elevate our team's standard practices
• Improve standards by setting an example with your hands-on experience and leadership

Senior Software Engineer, Resilience Engineering - DGX Cloud

Systems Engineer

• Ensure every DGX platform is ready for the full NVIDIA software stack—firmware, DGX OS, GPU drivers, CUDA toolkit, DCGM, DOCA/OFED, and management tools—as a validated, production-quality product.
• Own the GA SW/FW release process delivering firmware bundles, BaseOS ISOs, and release notes to OEM/OSV partners.
• Ensure platforms support AI agents like NemoClaw, Hermes agents, NIM microservices, and workloads customers expect out of the box.
• Lead development of the manageability firmware stack (BMC, BIOS) for all DGX platforms.
• Ensure firmware from partner teams (GPU, CPU, networking) integrates correctly at system level.
• Define validation strategy proving each DGX platform is production-ready: end-to-end system validation including firmware regression, NVQual certification, DL workload performance, OS/CUDA stack testing, multi-user scenarios, power/thermal validation, and field upgrade reliability.
• Establish quality gates and zero ship-stopper discipline.
• Drive platform bring-up for each new DGX system—coordinating first boot across new silicon (CPU, GPU), board design, and firmware teams.
• Own architectural strategy for next-generation platforms including firmware update mechanisms, system security posture, and AI application readiness.
• Ensure firmware release flows meet CSP and enterprise deployment requirements.
• Represent DGX platform readiness in executive reviews and strategic planning with VP/SVP leadership.
• Engage with industry standards bodies (DMTF Redfish, OCP).
• Own the complete DGX delivery lifecycle—system architecture, firmware development, integration, full-stack validation, GA release, and customer deployment—for every DGX product.
• Serve as single point of accountability for DGX platform readiness across NVIDIA—aligning GPU, CPU, networking, security, OS, and AI software teams to deliver on schedule.
• Own RCCA processes for field issues.
• Manage external vendor partnerships (AMI for SBIOS, BMC contributors) with clear quality gates and program tracking.
• Build and lead a world-class engineering organization.
• Mentor and develop leaders.

Manager, Distinguished Engineer – DGX Systems Software

Architect

• Modelling and analysis of graphics, LPU, SOC algorithms and features
• Lead cmodel chip execution end to end working with various stakeholder both internal and external
• Drive the next generation Infra initiatives
• Work in a team to document, design, develop tools to analyze and simulate, validate, and verify models
• Develop tests, test plans, and testing infrastructure for new architectures/features
• Code coverage analysis and reporting

SoC Modelling Architect

DevOps Engineer

• Work in a team of DevOps engineers supporting multiple software projects in the data science and AI domain, many of them open source
• Manage cutting-edge hardware and help inform purchasing decisions for the team
• Collaborate with build engineers, developers, and management to ensure the delivery of high-quality software
• Develop and modernize packages, such as streamlined Python wheels, for RAPIDS data science libraries
• Design and maintain container build processes
• Take a hands-on approach working with engineers on the team to implement DevOps best practices
• Execute on a range of DevOps initiatives including CI/CD, observability, security/legal compliance, and SysAdmin tasks
• Operate and maintain our infrastructure and development processes

Senior Engineer, Build and DevOps

Full-stack Engineer

• Involved in the definition, design, development and automation of innovative professional and consumer Linux Vulkan and OpenGL graphics software.
• Develop and maintain SW technologies targeted at enabling and supporting NVIDIA's GPU hardware.
• Ensure the best performance and feature quality running on cross platform implementations.
• Collaborate with test automation to achieve outstanding feature quality and timely identify regressions.
• Work with other worldwide internal teams, including software, hardware, architecture, and OEM support.

Software Engineer, Linux Graphics

• Work with a small team on a new kernel mode Linux driver that will support the latest generation of NVIDIA GPU's.
• Collaborate directly with the Linux kernel community to make patches in support of NVIDIA hardware.
• Influence the architecture and design of NVIDIA GPU kernel software to work well upstream.
• Represent NVIDIA GPU software to the open source community

System Software Engineering Lead

AI Engineer

• Develop the datasets and models for training and evaluating models and end-to-end systems for Content Safety, ProdSec, Robustness and ML Fairness
• Research and implement cutting-edge techniques for bias detection and mitigation in LLMs and systems using LLMs like RAGs
• Define and track key metrics for responsible LLM behavior and usage
• Follow the best MLOps practices of automation, monitoring, scale and safety
• Contribute to the MLOps platform and develop safety tools to help ML teams be more effective
• Collaborate with other engineers, data scientists, and researchers to develop and implement solutions to content safety and ML fairness challenges

Machine Learning Engineer, AI Safety

Scientist

• Apply fundamental and applied research to develop, train, fine-tune, and deploy advanced neural networks for language processing in agentic systems encompassing audio-visual reasoning, tool usage, and document understanding
• Advance post-training and alignment methods including instruction tuning, preference optimization, and RLHF/RLVR to improve multimodal agents for complex use cases
• Research and develop agentic reasoning and grounded perception capabilities, focusing on planning, tool execution, and long-horizon task completion across digital and physical environments
• Lead the collection, development, and benchmarking of multimodal datasets, ensuring high-quality evaluation of model accuracy, safety, and task completion success

Senior Deep Learning Scientist – Multimodal Agentic RL

Developer Relations

• Establish and sustain advanced technical expertise in AI and data processing for advanced MarTech solutions
• Collaborate multi-functionally to accelerate adoption of NVIDIA technologies, champion innovation, and define forward-looking standards
• Accelerate critically important workloads by architecting, demonstrating, and integrating the NVIDIA software stack into partner products
• Guide partners through complex onboarding and integration by providing advanced technical assets
• Engage senior technical leaders across partner organizations to promote best-practice integrations

Principal Developer Relations Manager – Marketing Technology

Artificial Intelligence

• Develop new opportunities and manage a portfolio of Intelligence Community programs, customers, and partners.
• Identify and help secure programs that expand the use of NVIDIA AI, networking, data center, and accelerated computing technologies.
• Work with government and industry leaders to align technology investments with operational and mission requirements.
• Build relationships across the Intelligence Community, national security organizations, research institutions, systems integrators, and contractors.
• Help customers evaluate and apply NVIDIA technologies to AI, data analytics, computer vision, secure computing, and high-performance computing workloads.
• Work with engineering, product, sales, and partner teams to support pilots, production deployments, and classified programs.
• Translate mission and operational requirements into practical technology and business plans.
• Travel as needed to customer locations, secure facilities, industry events, and NVIDIA offices.

Senior AI Strategist – Intelligence Community

• Build and deepen technical expertise in computer-aided engineering (CAE), serving as a technical advocate and trusted resource for developers in industrial engineering.
• Demonstrate and integrate NVIDIA’s software stack (tools, SDKs, libraries, NIMs, and blueprints) into real-world partner or developer projects to accelerate adoption.
• Support developers and partners through onboarding and integration by providing code samples, guides, demo pipelines, and hands-on assistance that enable CAE-specific use cases.
• Research and monitor developer ecosystem trends to identify opportunities for growth, sharing insights with engineering, product, and marketing teams to improve adoption strategies.
• Collaborate with partner technical leaders and internal engineering stakeholders to troubleshoot challenges, guide best-practice integrations, and feed technical takeaways back to NVIDIA teams.

Developer Relations Manager

Backend Engineer

• Design and implement idiomatic Rust libraries and APIs for foundational CUDA functionality and GPU algorithms
• Build safe Rust abstractions over native CUDA and C/C++ interfaces
• Develop and maintain the C/C++ components required to support Rust-facing functionality
• Establish safe and efficient interoperability between Rust and C/C++, including interfaces that support downstream Python integration
• Optimize performance across Rust, native C/C++, and GPU execution boundaries
• Own features end-to-end: design, implementation, testing, profiling, benchmarking, documentation, packaging, release, and maintenance
• Improve the Rust developer experience through examples, diagnostics, build integration, compatibility testing, CI, and collaboration with C/C++, Python, compiler, and runtime engineers
• Work with users to investigate and resolve issues related to safety, correctness, usability, compatibility, and performance.