Full-Time
Senior Deep Learning Frameworks Sustaining Engineer
Posted on 4/14/2026
NVIDIA
10,001+ employees
Designs GPUs and AI HPC platforms
Compensation Overview
$152k - $287.5k/yr
Company Historically Provides H1B Sponsorship
Santa Clara, CA, USA
In Person
 AI & Machine Learning (1) |
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- Bachelor of Science in Computer Science, Deep Learning, Artificial Intelligence, Applied Mathematics, or related field or equivalent experience
- 5+ years of relevant software development experience
- Excellent C/C++ programming and software design skills, including debugging and open source integration
- Python experience also helpful
- Utilizing tools involved in building software (Make, Docker, Bazel)
- Packaging systems (Debian, pip, npm, etc.)
- Build Systems (Gitlab, CI/Jenkins)
- Prior experience with machine learning algorithms and frameworks (TensorFlow, PyTorch, or MXNet)
- Ability to work independently, contribute to the stability of releases, and effectively communicate status to those involved in the release in a detail-oriented way
- Back-port changes from the mainline branch
- Keep track of open source dependency changes
- Ensure the latest stable dependencies are being used for enterprise products
- Actively contribute changes to support timely Long Term Support releases for TensorFlow, PyTorch, TensorRT products
- Fix customer reported bugs as part of release scope
- Integrate bug fixes found in mainline and work with other teams to ensure open source dependencies are patched for security vulnerabilities to address the needs of NVIDIA AI Enterprise business subscribers
- GPU programming experience (CUDA or OpenCL) desired but not required
- Experience with contributions to or managing large open source project - use of GitHub, bug tracking, branching and merging code, OSS licensing issues, managing patches, etc.
- Familiarity with GitLab CI pipelines
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
Simplify's Take
What believers are saying
- Agentic AI adoption at scale drives major inflection in inference demand globally.
- Jensen Huang projects $3T-$4T global AI factory buildout through 2030.
- Data centre networking revenue surged 263% YoY to $10.98B in Q4 FY2026.
What critics are saying
- Nemotron 3 open weights enable AMD and Intel to replicate NVIDIA's software moat.
- Insider selling over three months signals executive doubt about sustaining 73% growth.
- $30B OpenAI investment exposes NVIDIA to catastrophic losses from governance collapse.
What makes NVIDIA unique
- Vera Rubin launching July 2026 reduces inference token costs tenfold versus Blackwell.
- Nemotron 3 Nano Omni achieves 9x higher throughput on consumer hardware like RTX 4090.
- Clear datacenter product roadmap extends through 2028 with Feynman arriving in 2028.
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6 month growth
↓ -1%1 year growth
↓ -3%2 year growth
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Nvidia shares have climbed 18% over a ten-day winning streak, the longest since 2023. The stock is trading about 8% below its October all-time high of $212.19. CEO Jensen Huang revealed at last month's GTC conference that Nvidia has over $1 trillion in GPU orders through 2027, including Blackwell and next-generation Vera Rubin chips. Data centre revenue surged 75% year-over-year and now comprises 88% of the business, a dramatic shift from five years ago when gaming dominated. The rally follows major deals including Meta's February commitment to deploy millions of Nvidia chips across its global data centres. On Monday, Nvidia denied rumours it was pursuing acquisitions of PC makers Dell or HP. The company also unveiled Ising, a new family of open-source models for quantum computing.
D-Wave Quantum CEO Alan Baratz claims quantum computing poses a threat to Nvidia, citing superior energy efficiency. Speaking at the Semafor World Economy Summit, Baratz said D-Wave's quantum computer uses just 10 kilowatts of power—equivalent to five or 10 GPUs—whilst solving problems that would take GPU systems nearly a million years. D-Wave shares rose nearly 16% on Tuesday, part of a 140% gain over the past year. The company reported $2.75 million in Q4 revenue, missing analyst estimates, but bookings surged 471% to $13.4 million. The $5.3 billion company recently secured a $20 million agreement with Florida Atlantic University and acquired Quantum Circuits for $550 million. However, quantum machines remain specialised tools, unable to run large language models that drive Nvidia's dominance.
Vertiv Holdings has been reaffirmed with a Buy rating by Evercore ISI, setting a price target of $280, whilst Barclays raised its target from $281 to $300 with an Overweight rating. The electrical equipment company is partnering with Nvidia on AI infrastructure development. On 16th March, Nvidia introduced its Vera Rubin DSX AI Factory reference design, with Vertiv providing critical power and cooling solutions for AI data centres. The partnership integrates Vertiv's infrastructure expertise with Nvidia's AI systems to enhance energy efficiency and performance. Vertiv is developing Vertiv OneCore Rubin DSX, a prefabricated system designed to accelerate AI factory deployment. The Brussels-headquartered company specialises in critical digital infrastructure technologies for data centres and communication networks.
Nvidia and Dell Technologies are positioned as attractive AI infrastructure investments ahead of their May earnings reports, according to recent analysis. Both companies supply critical hardware for AI computing, with demand for AI capacity continuing to outpace available resources across major cloud services. Nvidia shares have remained flat for six months despite strong fundamentals. Last quarter, its data centre business generated $62 billion in revenue, up 75% year over year, with a 75% gross margin. The company expects over $1 trillion in cumulative orders for its Blackwell and upcoming Rubin chips through 2027. Trading at 17 times next year's expected earnings, Nvidia's valuation appears discounted relative to its 66% revenue growth in fiscal year 2026. Dell Technologies similarly stands to benefit from the AI infrastructure build-out. Both companies report earnings in May.