Technical Program Manager

We seek a Senior Technical Program Manager to handle daily operations for the Exemplar Performance Program. You will convert priorities into synchronized capacity, validation, debugging, and release plans across CSPs, NVIDIA Cloud Partners (NCPs), and internal engineering groups. Your role includes managing workstreams that cover Slurm and Kubernetes-based training and inference benchmarking, cross-partner debugging, release and QA coordination, PLC/OSRB alignment, and program visibility simultaneously. As the program expands into inference and agentic AI workloads, you will apply these methods to new stack complexities and partner engagements. You will collaborate directly with the program and Product lead to ensure execution aligns with Roadmaps. This position demands solid technical expertise, initiative, and the capability to work well with engineering, product, and partner-facing groups at different levels of the company. The ideal applicant has a deep understanding of cloud infrastructure and inference systems. They can ask insightful questions, lead investigations to resolution, and turn technical obstacles into concise action steps!

What You’ll Be Doing:

• Maintain the demand and allocation levels across platforms, GPU counts, topologies, and workloads; coordinate capacity reservations, access, readiness checks, and debug windows with cluster owners.
• Track cross-CSP performance investigations with engineering, SAs, and partner teams and build playbooks and pre-flight checks for repeat offenders.
• Maintain a coordinated achievement and coverage plan across recipes, frameworks, results tooling, and QA; follow up on MR reviews, merges, dependencies, and blocking regressions, and prepare release readiness summaries for each program increment.
• Help connect software roadmap execution to full-stack readiness, including dependencies across infrastructure, bring-up, validation, and downstream operational support.
• Standardize intake, debug handoffs, and release evidence practices; extend them from training into inference, K8s, and agentic benchmarking as priorities evolve.
• Establish engineering and product rhythm for Product Life Cycle (PLC) achievements and monthly release cadences.
• Identify multi-functional dependencies, mitigate risks, and drive resolution of complex technical and programmatic issues across partner, engineering, and product teams.
• Develop and maintain metrics for program efficiency and delivery health; collect and analyze data to support planning and data-driven decisions, and communicate progress clearly to senior leadership.

• 8+ years of technical program management experience. A Bachelor’s degree or equivalent experience to this in Computer Science, Electrical Engineering, AI, or a related field is required. You must have demonstrated ability to manage programs across multiple time zones and organizations.
• Practical knowledge of inference systems, cloud platforms, and distributed computing - sufficient to pose relevant technical questions and interpret engineering updates directly.
• Track record managing complex, multi-stakeholder programs in fast-paced software development environments, from kickoff through partner-facing delivery.
• Background in software release management, QA coordination, and platform validation cycles - preferably including compliance or review routines like open-source review, security review, or PLC/OSRB.
• Strong written communication skills; ability to write crisp, executive-ready program status updates and blocking issue memos that lead with signal, not noise.
• Experience with large-scale Agile tools and reporting (Jira, NVBugs, or equivalent) and comfort defining your own tracking structure when one doesn’t exist., * Strong background in Machine Learning, Deep Learning, and Artificial Intelligence applications, with familiarity with AI benchmarking tools, evaluation frameworks, or performance scorecards for large-scale GPU workloads!
• Experience working with LLM inference frameworks like vLLM, SGLang, or TensorRT-LLM, or knowledge of inference optimization methods such as speculative decoding, quantization, disaggregated prefill/decode, or multi-token prediction.
• Prior experience supporting CSP or NCP partner programs, including coordinating platform validations, cluster capacity requests, or performance bring-up across organizational boundaries.
• Kubernetes or cloud-native workload experience, with an understanding of how container orchestration affects GPU placement, scheduling, and workload repeatability.
• Experience with open-source software release procedures, including contributor licensing, OSRB-style assessments, and ecosystem readiness, to bring internal tooling public in a compliant, organized way.

Widely considered to be one of the technology world’s most desirable employers, NVIDIA offers highly competitive salaries and a comprehensive benefits package. As you plan your future, see what we can offer to you and your family www.nvidiabenefits.com