Full-Time

Senior Technical Program Manager

Deep Learning Frameworks

Deadline 7/27/26
NVIDIA

NVIDIA

10,001+ employees

Designs GPUs and AI HPC platforms

Compensation Overview

$168k - $322k/yr

+ Equity

Company Historically Provides H1B Sponsorship

Washington, USA + 5 more

More locations: Oregon, USA | Texas, USA | Santa Clara, CA, USA | Colorado, USA | Massachusetts, USA

Remote

Bachelor's

Category
AI & Machine Learning (1)
Engineering Management (1)
Business & Strategy (1)
Required Skills
Neural Networks
Git
JIRA
Confluence
Data Analysis

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Requirements
  • Postgraduate degree in Computer Science, Artificial Intelligence, Mathematics or equivalent experience.
  • 10+ years software program management experience including proven track record leading global projects, adaptable to multiple time zones in fast-paced software development environments.
  • Proven experience with delivering large software programs, spanning multiple layers of the software stack.
  • Ability to think strategically and tactically and to build consensus to make programs successful by engaging and moderating successful engagements with engineering and product teams.
  • Excellent communication, technical presentation, and attention to detail skills with a shown ability to multitask in a dynamic environment with shifting priorities and changing requirements.
  • Excellent organizational skills and ability to use project management tools (e.g. Jira, Aha!, Confluence) and distributed version control systems (e.g. Git)
Responsibilities
  • Collaborate with hardware, software, and model program managers, product managers and engineering teams to deliver Deep Learning Frameworks programs on existing and new hardware.
  • Engage with cross-company teams (hardware/software engineering, product, QA, compliance) and drive alignment on release scope, milestones, risk management, and dependencies.
  • Guide software programs in all aspects of program management – planning, forecasting, documenting, scheduling, effective meetings, multi-faceted prioritization, management of dependencies, reporting, and effective handling of critical and blocking issues.
  • Develop and implement metrics for measuring program effectiveness and improvement areas, collect and analyze data in support of planning and data driven decisions.
  • Define and implement standard processes for open-source contribution and release management within the Nvidia AI/ML ecosystem.
  • Report on overall program status, providing insights and recommendations to senior management.
  • Drive organizational alignment and efficiency by coordinating with multi-functional leads and streamlining processes.
Desired Qualifications
  • Experience with Deep Learning Frameworks (PyTorch, Jax, etc.), ML compilers (XLA, Triton, etc.), GPU Technology, open-source development.
  • Prior experience in production software development, release management, DevOps with a consistent track record of driving process improvements and measuring efficiency.
  • Exposure to NVIDIA GPU programming and software stack (CUDA Toolkit, cuDNN, TensorRT, NCCL, etc.).
  • Engineering background.

NVIDIA designs and manufactures graphics processing units (GPUs) and computing platforms used for gaming, data centers, and artificial intelligence. These products work by using parallel processing to handle complex mathematical calculations much faster than standard computer processors, supported by a software ecosystem that allows developers to build and run AI models. Unlike competitors that may focus solely on hardware, NVIDIA integrates its chips with specialized software and cloud services to create a complete environment for high-performance tasks. The company’s goal is to provide the underlying technology necessary to power advanced computing, from realistic video game graphics to autonomous vehicles and large-scale data analysis.

Company Size

10,001+

Company Stage

IPO

Headquarters

Santa Clara, California

Founded

1993

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Simplify Jobs

Simplify's Take

What believers are saying

  • NVIDIA reported $215.9 billion fiscal 2026 revenue, up 65%, on February 25, 2026.
  • The August 10, 2026 Wall Street financing pact opens more buyers for NVIDIA hardware.
  • Nemotron 3.5 Lightning boosts ecosystem lock-in while driving cheap GPU demand.

What critics are saying

  • US Commerce tightened China chip controls again on May 31, 2026.
  • The $500 billion financing push ties growth to GPU resale values and customer defaults.
  • An AI hardware glut from AMD, Huawei, or Chinese foundries crushes collateral and pricing.

What makes NVIDIA unique

  • CUDA remains the default software moat for AI training and deployment.
  • NVIDIA secured SK Hynix as its largest memory partner in June 2026.
  • Vera Rubin and Blackwell keep NVIDIA ahead in rack-scale AI systems.

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Benefits

Company Equity

401(k) Company Match

Growth & Insights and Company News

Headcount

6 month growth

0%

1 year growth

-2%

2 year growth

-3%
CNBC
Aug 12th, 2026
Nvidia taps Wall Street to raise $500B for AI infrastructure buildout

Nvidia has partnered with six US asset managers willing to raise $500 billion to finance AI infrastructure development. The chip giant is positioning AI infrastructure as a new asset class, with the plan hinging on GPUs retaining value over time like traditional hard assets rather than depreciating electronics. The approach carries risks. Ben Emons of FedWatch Advisors warned that Chinese manufacturers could flood markets with low-cost chips, potentially causing hardware prices to collapse and eroding collateral backing billions in private loans. Nvidia also launched Nemotron 3.5 Lightning, its first open-source AI model since CEO Jensen Huang advocated for open models. The lightweight model runs on a single GPU, potentially boosting chip sales by offering cheaper alternatives to proprietary models. Meanwhile, oil prices rose over 6% this week as prospects dimmed for a deal to increase traffic through the Strait of Hormuz.

Yahoo Finance
Aug 11th, 2026
Musk's 10GW SpaceX data centre plan could generate $300B in Nvidia orders or expose dangerous concentration risk

Elon Musk has announced plans to scale SpaceX data centres from 1.4 gigawatts to 10 gigawatts by 2027, working exclusively with NVIDIA hardware. Research firm SemiAnalysis estimates this could generate $150 billion to $500 billion in capital spending. The move could push NVIDIA shares towards $500, building on its $5.42 trillion market capitalisation and 92% data centre revenue share. NVIDIA recently announced a $500 billion financing partnership with Apollo, BlackRock, and other major firms to support AI infrastructure buildouts. However, the proposal creates significant concentration risk. SpaceX would propose capital expenditure rivalling Amazon Web Services and Google combined, whilst being far less profitable. NVIDIA already holds $119 billion in supply commitments. If SpaceX funding tightens or hyperscale customers slow orders, the stock could face substantial downside risk. Meanwhile, AMD has surged 121% year-to-date versus NVIDIA's 17% gain.

Cointime
Aug 11th, 2026
AI startup Trajectory raises $40M at $300M valuation led by Sequoia Capital

AI infrastructure startup Trajectory has raised $40 million at a $300 million post-money valuation, led by Sequoia Capital with participation from Nvidia and Bessemer, according to The Information. The funding comes just two months after the company secured a $15 million seed round at a $115 million valuation. Founded in May by former Google DeepMind researchers Ronak Malde and Michael Elabd, alongside ex-Apple researcher Arjun Karanam, Trajectory focuses on continuous learning technology. The platform transforms user corrections, retries and edits into training signals, enabling AI models to improve after deployment. The company automates this process, allowing enterprises to continuously adjust models, prompts and harnesses based on real usage data. Clay, Decagon and Harvey are currently using or testing the technology.

Yahoo Finance
Aug 11th, 2026
Nvidia develops Nemotron 4 open-source AI model with 1T+ parameters

Nvidia is developing Nemotron 4, a new AI model family aimed at rivaling top open-source models globally, The Information reported. The largest model is expected to have at least 1 trillion parameters, according to employees working on the project. Nvidia has not set a release date, though the model could be ready as early as late autumn. The company has yet to complete final training. Separately, Nvidia unveiled Nemotron 3.5 Lightning for tasks including code review and security monitoring. It also released NeMo Switchyard, an open-source model-routing library. The chip giant is among few major US firms releasing open-source models, which have gained attention as AI costs rise and Chinese models approach capabilities of systems from Anthropic and OpenAI.

CNBC
Aug 11th, 2026
Nvidia releases first open-source AI model after CEO Huang's open letter debut

Nvidia has released Nemotron 3.5 Lightning, its first open-source AI model since CEO Jensen Huang entered the open-source AI debate. The model was developed particularly for autonomous AI agents and will be available on HuggingFace and Nvidia's website. Huang previously argued that open-weight models allow companies greater control, spur competition, and bring down pricing. For Nvidia, open-source AI boosts chip sales, as the models still require GPUs to run. Companies including CodeRabbit and Harvey have tested the model. Nvidia also released NeMo Switchyard software to determine the most appropriate and cost-effective AI model for specific tasks. Nvidia used distillation techniques to give Nemotron 3.5 Lightning capabilities similar to its larger models.