NVIDIA

Mechanical Engineer

• Architecting the clock domain to satisfy functional, physical and testing design requirements.
• Engage with multiple teams and design the GPU or CPU clocks.
• Improve Power, Performance, and Area (PPA) of NVIDIA chips by evaluating trade-offs.
• Collaborate with Physical design and timing team to evaluate Clocking concerns.
• Deliver clock RTL information to GPU, CPU and SOC verification team, timing and DFT teams.
• Get involved in end-to-end cycle of ASIC execution starting from micro-arch.

ASIC Clocks Design Engineer – New College Grad

Full-stack Engineer

• Build innovative features for NVIDIA's GPU profiling tools from inception to execution
• Incorporate new hardware profiling capabilities into tools and workflows
• Work independently based on high-level requirements, filling in build details and making sound engineering decisions
• Collaborate with architects, performance engineers, and other software teams to understand requirements and deliver solutions
• Improve and maintain a large, evolving codebase with high standards for quality and reliability

Software Engineer, GPU Performance Tools

Architect

• Develop innovative architectures to extend the state of the art in deep learning performance and efficiency
• Analyze performance, cost and power trade-offs by developing analytical models, simulators and test suites
• Understand and analyze the interplay of hardware and software architectures on future algorithms, programming models and applications
• Evaluate PPA (performance, power, area) for hardware features and system level architectural trade-offs.
• Develop high level simulators in C++/Python
• Actively collaborate with software, product and research teams to guide the direction of deep learning HW and SW

Senior Deep Learning Performance Architect

LLM Engineer

• Bring up, validate, and debug large-scale AI clusters, infrastructure, and end-to-end workloads.
• Bring up, tune, and benchmark AI pre-training, post-training, and inference workloads using PyTorch, NeMo / Megatron, TensorRT-LLM, and adjacent NVIDIA AI software stacks.
• Perform root-cause analysis of failures in large distributed environments.
• Contribute to the resilience and failure-attribution tooling that detects, triages, and attributes node, fabric, and workload failures across the cluster.
• Build and maintain repeatable benchmark suites, automation, acceptance criteria, and qualification workflows on new platforms.
• Tune runtime settings, communication parameters, and deployment configurations in close partnership with framework, systems, and platform teams.
• Deliver actionable, data-driven recommendations based on profiling, benchmark results, and cluster characterization.

Software Engineer, DGX Cloud AI Infrastructure

• Design, develop and optimize server application responsible for managing NVLink networks of thousands of network devices!
• Collaborate with multiple teams in our multi-functional environment on developing new features and improvements
• Participate in the design and architecture of new next generation network solutions for super computers
• Manage issues during integration, testing, deployment & QA
• Work and collaborate with team members in different geographical locations

Senior Software Engineer, Subnet Management

• Own and improve the end-to-end path for deploying Warp-based robotics and simulation components onto embedded platforms such as Jetson.
• Build and maintain reproducible deployment workflows including cross-compilation, CI, packaging, and containerized delivery for embedded robotics targets.
• Optimize on-device performance under real constraints including latency, throughput, memory footprint, thermals, and power.
• Debug complex issues across the stack spanning Python, C++, CUDA, drivers, and embedded Linux, including hard-to-reproduce device-specific failures.
• Integrate Warp components into robotics applications and frameworks, including ROS 2 and Isaac-based stacks, and work with partner teams to unblock adoption.
• Develop system-level testing, validation, and performance regression infrastructure for embedded targets.
• Collaborate with compiler, runtime, and kernel engineers to improve portability and performance across GPU architectures and embedded configurations.

Senior Software Engineer – NVIDIA Warp

• Lead bring-up, validation, and debugging of large-scale AI clusters, infrastructure, and end-to-end workloads, setting the standard for how the team operates.
• Bring up, tune, and benchmark AI pre-training, post-training, and inference workloads using PyTorch, NeMo / Megatron, TensorRT-LLM, and adjacent NVIDIA AI software stacks.
• Profile and optimize end-to-end workload performance across compute, memory, networking, and communication layers using tools such as Nsight Systems, NCCL tests, and custom microbenchmarks.
• Analyze scaling efficiency for distributed LLM workloads using data, tensor, pipeline, and expert parallelism across modern GPU clusters, and translate findings into concrete tuning guidance.
• Own root-cause analysis of complex failures — hangs, performance regressions, topology sensitivity in large distributed environments.
• Define and build the resilience and failure-attribution stack: detecting, triaging, and attributing node, fabric, and workload failures across the cluster at scale.
• Build repeatable benchmark suites, automation, acceptance criteria, and qualification workflows on new platforms.
• Tune runtime settings, communication parameters, and deployment configurations in close partnership with framework, systems, and platform teams.
• Deliver actionable, data-driven recommendations based on profiling, benchmark results, and cluster characterization.
• Mentor engineers, drive technical standards, and act as a force multiplier across the broader performance and infrastructure organization.

Senior Software Engineer, DGX Cloud AI Infrastructure

Engineer

• Analyzing deep learning networks and developing compiler optimization algorithms
• Collaborating with deep learning framework and hardware architecture teams to accelerate software
• Defining public APIs and implementing compiler infrastructure techniques for neural networks

Senior Compiler Engineer – DL

• Design and implement Python-first APIs, SDK workflows, and plugin interfaces for building, measuring, and improving agents across multiple runtimes and product surfaces
• Build reusable systems for observing behavior, measuring progress, detecting regressions, and turning runtime evidence into product decisions
• Build systems for ingesting, normalizing, validating, and analyzing agent execution data and evaluation datasets
• Partner with research, product, platform, and infrastructure teams to integrate agentic capabilities broadly across NVIDIA agent runtimes and developer workflows
• Help turn emerging agent development and improvement techniques into reliable, reusable product capabilities
• Improve reliability, observability, debuggability, and performance across NeMoStack services, SDKs, plugins, jobs, and developer workflows
• Build strong test coverage across unit, integration, E2E, Docker, and Kubernetes workflows
• Drive 'speed of light' engineering: fast iteration, high ownership, pragmatic decisions, and performance-minded implementation under production constraints
• Provide senior technical leadership through design reviews, code reviews, mentoring, and ownership of ambiguous cross-component problems

Senior Software Engineer, Agentic Systems

Operations

• Establish the site’s operating model, mission, and performance rhythm to align with NVIDIA’s broader manufacturing and supply objectives.
• Partner to lead day-to-day site operations, coordinating people, resources, and factory interfaces to ensure build plans are accomplished, and supply commitments are protected.
• Serve as the primary NVIDIA contact for Houston-area manufacturing partners, addressing operational and business issues in a structured and timely manner.
• Provide leadership during factory disruptions, emergency response situations, and recovery efforts, ensuring clear communication, addressing critical issues, and restoring stable operations.
• Build and develop the Texas operations team, including workforce planning, hiring, mentoring, and performance management.
• Foster a culture grounded in accountability, collaboration, and continuous improvement.
• Partner with internal functions across planning, engineering, quality, materials, IT and logistics to align working models, tools, important metrics, and resource plans.
• Act as a senior point of contact when cross-functional alignment is required.
• Coordinate continuity of supply assurance processes, including forecast acceptance alignment and execution through delivery of finished goods into NVIDIA-managed distribution and customer-owned hubs.
• Manage site-level budgets and resources responsibly, ensuring operational investments support performance, resiliency, and long-term scalability.
• Provide regular, clear reporting on operational performance, risks, and recovery actions to senior leadership.

Senior Manager, Manufacturing Operations

Solutions Engineer

• Collaborate with other teams to plan and implement data center infrastructure solutions based on NVIDIA Datacenter reference architecture, including power distribution, cooling systems, network architecture, server hardware, and storage systems.
• Plan and manage deployment of NVIDIA's pioneering AI infrastructure solutions including highly complex rack-scale, liquid cooled compute and networking hardware systems, in a fluid and fast paced environment.
• Conduct pre-deployment planning including reviewing cluster and data center architecture, plan network port mapping and fiber optic cabling BOM, identify potential risks, train vendors and find areas for improvement.
• Evaluate customers' and partners' infrastructure design proposals for consistency with industry standards and regulatory requirements.
• Provide feedback and recommendations to improve performance, scalability, and cost-effectiveness.
• Perform testing, troubleshooting and validation of compute systems based on collaboration with product and engineering teams.
• Act as the NVIS mentor providing guidance, mentorship, and support to ensure the NVIS team's success in their respective roles.
• Establish and enforce quality assurance processes to verify that deployments meet established specifications and performance benchmarks.
• Conduct thorough bring-up, testing, and validation to validate the functionality and reliability of infrastructure components.
• Drive continuous improvement initiatives to enhance data center infrastructure efficiency for NVIDIA data center reference architecture and deployment blueprint, resilience, and sustainability.
• Find opportunities to streamline processes, automate repetitive tasks, and leverage emerging technologies to optimize infrastructure operations.

Solutions Architect, Data Center Infrastructure

Technical Program Manager

• Ensuring that from engineering sample to mass production, that NVIDIA is ready to support with tooling, processes and lessons learned which are implemented and available for internal and external roll out.
• Program management of the status for hardware, software, tooling, and process are defined.
• Lead customer engagement and communication, coordinating planning, and activity preparation.
• Quality Assurance: Establish and implement quality assurance processes to verify that deliverables meet established specifications and quality requirements.
• Continuous Improvement: Drive initiatives to improve efficiency through automation, tooling, and other means to increase speed and accuracy of readiness planning.
• Partnership and Communication: Collaborate and communicate across internal teams and customers to facilitate the seamless integration of our readiness capabilities.

Technical Program Manager – New Product Readiness

• Design and develop innovative AI-driven web products to solve big data challenges in chip design.
• Build high performance API's, data pipelines and backend services in a distributed systems environment.
• Own technical strategy for broad and complex challenges.
• Collaborate closely with product and engineering teams to translate high-level requirements into actionable deliverables.
• Handle multiple tasks and adapt to changing priorities.
• Be an engineering generalist.
• Discover and build skills needed at different times to solve the problems at hand.

Senior Software Engineer, AI Web Products

DevOps Engineer

• Working on building tools to improve the SRE Observability.
• Be part of the Kubernetes migration journey with VMI setup and problem solving.
• Rapidly debug and triage incidents and user-reported issues
• Taking ownership of automating, scripting, and tooling of new/existing scripts to help the team achieve 100% automation of daily tasks
• Support services before they go live through activities such as system design consulting, developing software platforms and frameworks, capacity management and launch reviews.
• Be part of an on call rotation to support production systems

Senior Site Reliability Engineer, GeForce NOW

• Own system architecture for inference stack and other applications running on this class of products
• Co-architect with the orbital hardware system architecture team
• Define the manageability architecture for an unreachable, autonomous data center
• Architect rad-tolerant system software behaviors
• Drive Redfish, MCTP, PLDM, and constellation-level management protocols
• Partner with cloud and constellation customers to translate mission requirements
• Drive reliability and optimization in the system software architecture
• Own quality, reliability, and telemetry performance of the system software