Full-Time
Senior Software Engineer
NVIDIA
10,001+ employees
Designs GPUs and AI HPC platforms
No salary listed
Company Historically Provides H1B Sponsorship
California, USA + 2 more
More locations: Santa Clara, CA, USA | United States
Hybrid
 DevOps & Infrastructure (1) |
|---|
- A degree in Computer Science, Computer Engineering, or a related field (BS or MS) or equivalent experience.
- 6+ years building production software with a strong focus on containers and Kubernetes.
- Strong Python skills building production-grade tooling/services
- Experience with Python SDKs and clients for Kubernetes and cloud services
- Expert knowledge of Docker/BuildKit, containerd/OCI, image layering, multi-stage builds, and registry workflows.
- Deep experience operating workloads on Kubernetes.
- Hands-on experience building and running GPU workloads in k8s, including NVIDIA device plugin, MIG, CUDA drivers/runtime, and resource isolation.
- Excellent collaboration and communication skills; ability to influence cross-functional design.
- Design, build, and harden containers for NIM runtimes, inference backends; enable reproducible, multi-arch, CUDA-optimized builds.
- Develop Python tooling and services for build orchestration, CI/CD integrations, Helm/Operator automation, and test harnesses; enforce quality with typing, linting, and unit/integration tests.
- Help design and evolve Kubernetes deployment patterns for NIMs, including GPU scheduling, autoscaling, and multi-cluster rollouts.
- Optimize container performance: layer layout, startup time, build caching, runtime memory/IO, network, and GPU utilization; instrument with metrics and tracing.
- Evolve the base image strategy, dependency management, and artifact/registry topology.
- Collaborate across research, backend, SRE, and product teams to ensure day-0 availability of new models.
- Mentor teammates; set high engineering standards for container quality, security, and operability.
- Expertise with Helm chart design systems, Operators, and platform APIs serving many teams.
- Experience with OpenAI API, Hugging Face API as well as understanding difference inference backends (vLLM, SGLang, TRT-LLM)
- Background in benchmarking and optimizing inference container performance and startup latency at scale.
- Prior experience designing multi-tenant, multi-cluster, or edge/air-gapped container delivery.
- Contributions to open-source container, k8s, or GPU ecosystems.
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
↓ -2%Matlantis has integrated NVIDIA's ALCHEMI Toolkit into its materials simulation platform to accelerate industrial materials discovery. The company previously incorporated NVIDIA Warp-optimised kernels, achieving up to 10x speed improvements in atomistic calculations. The integration includes LightPFP, Matlantis' lightweight potential for large-scale simulations, which uses a server-based architecture with NVIDIA ALCHEMI Toolkit-Ops to reduce communication bottlenecks. Matlantis plans to integrate its flagship Universal Machine-Learning Interatomic Potential with the toolkit to further enhance GPU efficiency. Launched in 2021, Matlantis is a cloud-based atomistic simulator jointly developed by PFN and ENEOS. The platform uses deep learning to increase simulation speeds by tens of thousands of times and serves over 150 companies discovering materials including catalysts, batteries and semiconductors.
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.