NVIDIA

Technical Program Manager

• Define and drive schedules, surface dependencies before they block work, and own multi-functional alignment from architecture review through tape-out.
• Accountable for delivery, not only oversight.
• Participate in critical design reviews, flag scope and integration risks early, and make trade-off calls others depend on — schedule vs. quality, coverage vs. velocity, design change vs. firmware workaround.
• Act as the primary technical link across silicon, systems, software, operations, and marketing.
• Identify technical and schedule risks early, build mitigations with engineering, and move work forward with clarity and context.
• Capture lessons from completed programs and put in place changes that measurably improve speed, quality, and predictability — not just documentation of what happened.

Senior Technical Program Manager – Silicon Co-design

Hardware Engineer

• Build, architect, develop, and debug critical firmware running in the GPU OOBHUB, prioritizing robust peripheral control and secure communication interfaces.
• Build and optimize high-reliability firmware update mechanisms and telemetry systems for next-generation GPU subsystems.
• Collaborate closely with hardware architects and ASIC designers to initiate new silicon, defining firmware-hardware interfaces and communication protocols.
• Implement secure, modern firmware solutions, bringing to bear high-reliability languages and principles to ensure system stability.
• Partner with internal software, hardware, and infrastructure teams to transform brand new architectural features from concepts into production-ready firmware.

Senior Firmware Engineer – GPU

Client Partner

• Gain strategic alignment with OEM Channel, GSI, leadership & resources and influence their plans & investments w/ the partner ecosystem to proliferate NVIDIA SW & solution stacks through them
• Focus on specific OEM partners with services capabilities including SDPs, GSIs and key Solution Providers to demonstrate NVIDIA SW & OEM solutions to deliver AI Infrastructure and application services offerings to Enterprises
• Develop a trusted advisor relationship with OEM partner leadership
• Plan regular business reviews, EBCs to help update & keep them current on latest NVIDIA trends, technologies and messaging
• Identify & align leaders/teams on a focused set of partners & joint programs to drive pipeline, and incremental sales
• Identify enablement needs, align OEM+NVIDIA resources and & engage with the Field Sales teams at channel partners and ensure AI capability readiness through AI Advisors, Roadshows, Webinars, Virtual Events, etc.
• Work w/ OEM & NVIDIA cross functional teams to produce executable plans, with joint investments that improve value for NVIDIA via incremental pipeline & revenue
• Develop programmatic approach to scaling out ISV based AI solutions in key industry segments through target partners
• Continual personal development is required in this very fast-moving market
• Keep up to date with the latest technological developments particularly with respect to AI Enterprise Workflows and Software
• Also, key to keep pace with partner ecosystem (NVIDIA Partner Network) and Industry partner trends

Partner Development Manager

SEO Marketing

• Design, implement, and maintain CI/CD pipelines for building OS images across Ubuntu and RHEL distributions
• Build unit testing and integration testing frameworks using Go and Python
• Optimize CI/CD infrastructure using Jenkins and GitlabCI
• Implement infrastructure as code with Terraform and work with Kubevirt for virtualized workloads
• Create and maintain Ubuntu and RHEL packaging solutions (deb/rpm)
• Identify infrastructure improvements and implement metrics gathering systems for KPIs and dashboards
• Champion automation initiatives to achieve 100% end-to-end automation across developer and release workflows

Senior Software Engineer – BaseOS

Architect

• Developing architecture and micro-architecture to improve the state-of-the-art in GPU memory system and memory management
• Participating in performance simulation of features to improve memory access efficiency
• Implementing and maintaining high-level functional and performance models
• Analyzing benchmarks, application workloads and performance simulation results to identify areas for microarchitecture optimizations
• Defining and performing experiments to study the machine in action, presenting experiment results to the larger group and proposing mechanisms for improvement
• Creating architectural specifications and customer-facing documents
• Debugging performance and functional issues with high-level models, RTL simulation, and silicon

Senior GPU Memory Architect

• Study workloads for a wide range of markets, including CSP, HPC, AI / DL, and autonomous vehicles.
• Develop infrastructure to visualize CPU performance bottlenecks on important workloads.
• Develop performance analysis tools.
• Analyze and debug performance scaling bottlenecks on multi-core and multi-socket CPU and CPU/GPU systems.
• Work with CPU architects to improve future CPU and system designs based on findings.

Senior CPU Performance Architect

Product Designer

• Drive end-to-end UX design for developer and creative tools, from discovery through delivery, shaping experiences that simplify complex workflows
• Generate deep user insights through contextual inquiry, surveys, focus groups, and direct engagement in beta communities
• Translate research findings into intuitive user flows, wireframes, and interactive prototypes, leveraging AI-powered design tools
• Lead usability testing efforts to validate concepts and refine both prototypes and implemented experiences
• Partner closely with engineering and product teams to ensure design intent is preserved through development
• Contribute to scalable, high-quality experiences by maintaining design system consistency and strong usability standards

Senior UX Designer, Cloud User Experience

Full-stack Engineer

• Drive platform bringup, feature enablement, end-to-end software validation, and debug for next-generation NVLink-based GPU and rack-scale systems.
• Develop tools, diagnostics, automation, and infrastructure for system validation, regression testing, and fleet support.
• Lead reliability and MTBI validation through stress testing, telemetry analysis, failure injection, and issue resolution.
• Triage complex software, firmware, networking, and platform issues across validation, deployment, and production environments.
• Collaborate with architecture, hardware, firmware, software, and Customer engagement teams to improve system quality and reliability.
• Build and maintain SRE-style validation infrastructure, including provisioning, monitoring, and operational readiness.
• Create automation, dashboards, runbooks, and debug workflows that improve root-cause analysis and operational efficiency.

Senior Software Engineer – NVLink Rack Scale Stability and Reliability

• Lead the complete implementation of DGX Cloud software initiatives
• Partner with software, infrastructure, product, and platform engineering teams
• Lead initiatives involving Kubernetes-based platforms, cloud-native services
• Define and implement scalable program management processes
• Identify cross-functional dependencies, mitigate risks
• Establish clear success metrics and reporting mechanisms
• Foster a culture of collaboration and continuous improvement
• Report on overall program status, providing insights and recommendations
• Drive organizational alignment and efficiency

Senior Technical Program Manager, DGX Cloud Software Products and Service

Frontend Engineer

• Build and implement critical features for core NGC services
• Play a key role in developing the unified portal for NVIDIA cloud products
• Proactively apply AI tools and agents to boost code quality and system stability
• Drive the evolution of application architecture and development patterns
• Work closely with Product, UX, and Backend teams to create user-friendly UIs
• Participate in all stages of the product lifecycle
• Estimate personal timelines and coordinate work
• Present and/or demonstrate your work/research

Frontend Software Engineer

AI Engineer

• Design, build and optimize agentic AI systems for the CUDA ecosystem
• Co-design agentic system solutions with software, hardware and algorithm teams; influence and adopt new capabilities as they become available
• Develop reproducible, high-fidelity evaluation frameworks covering performance, quality and developer productivity
• Collaborate across the AI stack—from hardware through compilers/toolchains, kernels/libraries, frameworks, distributed training, and inference/serving—and with model/agent teams

Senior AI Engineer, High Performance

Application Engineer

• Provide onsite support for large datacenter deployments of NVIDIA AI solutions.
• Solving complex hardware and deployment issues
• Be a technical specialist on GPU and networking products directly supporting sales account managers, working closely with the team to deliver outstanding AI datacenter solutions.
• Actively establish the technical relationship with our customer’s engineers, management, and architects at focus accounts.
• Identify customer architectures and key product requirements in the enterprise AI market.
• Provide technical and sales training to the direct sales team and channel partners.
• Establish strong relationships and communication channels with internal teams.

Field Application Engineer, New College Graduate

• Collaborate with software and hardware teams to identify high-impact opportunities for applying agentic AI technologies.
• Lead the design, development, and optimization of agentic AI solutions that address challenges in performance, quality and productivity.
• Develop and maintain agentic AI benchmarks to evaluate performance across diverse use cases.

Senior AI Architect, Computer Use Agents

Engineer

• Analyze full‑chip and unit‑level power using internal and industry‑standard RTL and gate‑level power tools, and translate data into concrete design and architectural improvements.
• Develop and productionize power‑aware models and flows, including ML/RL‑based techniques for anomaly detection, dynamic power management, and design‑space exploration.
• Design and train new LLMs that “learn the art” of power analysis from design data, power reports, bug histories, and best practices—so they can:
• Assist engineers in interpreting complex power data
• Propose likely root causes and candidate fixes
• Recommend architectural and micro‑architectural optimizations for power
• Perform comparative power analysis across workloads, products, and design options to identify trends, anomalies, and optimization opportunities that aren’t obvious from first principles alone.
• Partner closely with Architects, Performance, Software, ASIC Design, and Physical Design teams to interpret power data, root‑cause power bugs, and drive fixes and design changes.
• Prototype and evaluate new architectural features in Verilog, with a strong focus on their power and energy implications.
• Automate and scale flows (Python/Perl/C++), and define new pipelines that fast‑track power anomaly detection and close the loop between power data, AI models, and design decisions.
• Apply AI to power optimization: build and deploy data‑driven models—using machine learning, reinforcement learning, data analytics, and custom LLMs—to recommend or automatically tune power‑efficient configurations and policies.

Senior Power Analysis and Optimization Engineer

• Guide the system build initiatives encompassing research, composition, and development of RAN algorithms within the realms of 5G/6G PHY and MAC-Scheduler, integrating innovative strategies like AI/ML, Deep Learning, and Raytracing.
• Enable realization of algorithms in a GPU accelerated system, carefully assessing the design and implementation tradeoffs.
• Effectively work with customers and ecosystem partners and support integration, system simulations, performance benchmarking, and optimizations.