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.
What We Need to See
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.
Ways to Stand Out from the Crowd
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/
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 6, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.
NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.
