Role at a glance
- Salary
- $168K – $322K/yr
- Location
- Santa Clara, California, United States
- Work arrangement
- On-site
- Employment
- Full-time
- Experience
- 7+ years of technical program management or closely related experience in AI/ML platforms, distributed systems, cloud infrastructure,...
- Education
- BS/MS/PhD in Electrical Engineering, Computer Science, Computer Engineering or similar (or equivalent experience).
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Role Summary
The Technical Program Manager will lead recurring capacity operations for large-scale AI infrastructure programs and support tooling and automation initiatives. The role builds operating mechanisms that make demand, supply, readiness, risks, decisions, and delivery work visible and moving across engineering, research, infrastructure, and other collaborating teams.
What You'll Do
- Own intake, triage, routing, and request-quality standards for accelerator-capacity requests across engineering and research teams.
- Run quarterly and annual demand forecasts, change control, review preparation, and follow-through.
- Prepare capacity-planning and allocation reviews using demand, supply, commitments, readiness, timing, and priorities.
- Track capacity from request and forecast through delivery, readiness, assignment, and productive use.
- Coordinate infrastructure dependencies including access, storage, data movement, networking, readiness checks, migration timing, and...
- Maintain dashboards and source-data quality, operating cadences, action logs, dependency tracking, decision records, risk registers, and...
Generated from the employer's posting. Verify important details before applying.
View full postingQualifications
Technical program management experience in AI/ML platforms, distributed systems, cloud infrastructure, compute capacity, or technically demanding engineering environments; experience with forecasting, dependency management, decision and risk records, data quality, dashboards, and cross-functional program operations.
Required
- BS/MS/PhD in Electrical Engineering, Computer Science, Computer Engineering or similar, or equivalent experience
- 7+ years of technical program management or closely related experience
- Experience owning recurring operational programs with scarce-resource trade-offs, multiple cadences, executive clarity, and overlapping...
- Experience with intake, forecasting, review preparation, dependency management, decision and risk records, action closure,...
- Technical proficiency with infrastructure constraints, requirements, and metrics
- Data proficiency with source quality, dashboards, reconciliation, operational measures, and ownership gaps
- Excellent written and verbal communication
- Ability to influence without authority across research, platform engineering, infrastructure, data, finance, operations, and leadership...
Preferred
- Experience with GPU or other accelerator-capacity planning, utilization programs, cluster operations, workload bring-up, or large-scale...
- Experience with demand and supply roadmaps, normalization across accelerator types, allocation reviews, quota or priority management,...
- Familiarity with batch scheduling, cluster-management, cloud, or data-center environments and workload-readiness dependencies
- Experience with observability or dashboard platforms, data-quality controls, and automated reporting for infrastructure or service...
- Experience driving API-enabled workflow automation or decision-support tools with human approval gates, audit evidence, and safe...
Original job description
Content provided by the employer
Original job description
Content provided by the employer
We are seeking a Technical Program Manager to lead recurring capacity operations for large-scale AI infrastructure programs and support tooling and automation initiatives! You will build the mechanisms that keep demand, supply, readiness, risks, decisions, and delivery work visible, sequenced, detailed, and moving.
This is an operational leadership role, not a meeting-coordination role. You will challenge incomplete inputs, establish operating cadences, turn ambiguous constraints into clear decisions, and close cross-functional actions - partnering with, not replacing, technical owners.
What you will be doing:
Own intake, triage, routing and request-quality standards for accelerator-capacity requests across multiple engineering and research teams.
Run quarterly and annual demand forecasts, change control, review preparation, and follow-through; identify late, incomplete, or conflicting inputs early.
Prepare capacity-planning and allocation reviews using demand, available supply, prior commitments, readiness, workload timing, and business priorities.
Track capacity through its operational lifecycle—from request and forecast through delivery, readiness, assignment, and productive use.
Coordinate infrastructure dependencies such as access, storage, data movement, networking, readiness checks, migration timing, and provider or provisioning tickets.
Maintain dashboards and source-data quality, including freshness checks, ownership for missing inputs, reconciliation, and retirement of repeated manual reporting.
Own operating cadences, agendas, action logs, dependency tracking, decision records, risk registers, blocking issue paths, and closure difficulty.
Prepare concise leadership reporting that distinguishes facts, risks, decisions needed, options, recommended paths, accountable owners, and due dates.
What we need to see:
BS/MS/PhD in Electrical Engineering, Computer Science, Computer Engineering or similar (or equivalent experience).
7+ years of technical program management or closely related experience in AI/ML platforms, distributed systems, cloud infrastructure, compute capacity, or another technically demanding engineering environment.
Shown ownership of recurring operational programs with scarce-resource trade-offs, multiple cadences, executive clarity, and overlapping peak periods.
Strong program mechanics: intake compose, forecasting, review preparation, dependency management, decision and risk records, action closure, documentation, and status communication.
Enough technical proficiency to understand infrastructure constraints, ask detailed questions, inspect requirements and metrics, and work credibly with engineers and researchers.
Data proficiency sufficient to evaluate source quality, interpret dashboards, reconcile conflicting views, define useful operational measures, and identify missing ownership.
Consistent track record to transform ambiguous cross-functional work into a durable operating system with clear owners, decisions, and critical issue paths with excellent written and verbal communication, including the ability to turn sophisticated updates into concise decisions, risks, options, actions, and leadership mentorship.
Ability to influence without authority across research, platform engineering, infrastructure, data, finance, operations, and leadership collaborators!
Ways to stand out from the crowd:
Experience with GPU or other accelerator-capacity planning, utilization programs, cluster operations, workload bring-up, or large-scale AI training and inference environments.
Experience with demand and supply roadmaps, normalization across accelerator types, allocation reviews, quota or priority management, and capacity migrations.
Familiarity with batch scheduling, cluster-management, cloud, or data-center environments and the operational dependencies that affect workload readiness.
Experience with observability or dashboard platforms, data-quality controls, and automated reporting for infrastructure or service operations.
Experience driving API-enabled workflow automation or decision-support tools with explicit human approval gates, audit evidence, and safe operating controls.
You will also be eligible for equity and benefits.
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.#deeplearningAbout the company
NVIDIA
Large Enterprise
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.
NVIDIA is a leading technology company renowned for its graphics processing units (GPUs) and innovative computing solutions that enhance visual experiences across multiple platforms, including gaming, scientific research, and artificial intelligence. Founded in 1993, the company has expanded its offerings to include powerful AI frameworks and deep learning platforms, making significant contributions to industries such as gaming, data centers, automotive, and healthcare. NVIDIA's commitment to pushing the boundaries of visual computing continues to drive advancements in both hardware and software, positioning the company at the forefront of emerging technologies and digital transformation.