NVIDIA Logo

NVIDIA

Senior System Software Engineer - GPU Performance

Reposted 28 Days Ago
In-Office or Remote
Hiring Remotely in Santa Clara, CA, USA
148K-288K Annually
Mid level
In-Office or Remote
Hiring Remotely in Santa Clara, CA, USA
148K-288K Annually
Mid level
Conduct performance analysis on large multi-GPU clusters, evaluate interactions between libraries and hardware, and develop tools for performance visualization and data analysis.
The summary above was generated by AI

NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services. Our work opens up new universes to explore, enables amazing creativity and discovery, and powers what were once science fiction inventions from artificial intelligence to autonomous cars.

We are the GPU Communications Libraries and Networking team at NVIDIA. We deliver libraries like NCCL, NVSHMEM, UCX for Deep Learning and HPC. We are looking for a motivated Performance engineer to influence the roadmap of our communication libraries. The DL and HPC applications of today have a huge compute demand and run on scales which go up to tens of thousands of GPUs. The GPUs are connected with high-speed interconnects (eg. NVLink, PCIe) within a node and with high-speed networking (eg. Infiniband, Ethernet) across the nodes. Communication performance between the GPUs has a direct impact on the end-to-end application performance; and the stakes are even higher at huge scales! This is an outstanding opportunity for someone with HPC and performance background to advance the state of the art in this space. Are you ready for to contribute to the development of innovative technologies and help realize NVIDIA's vision?

What you will be doing:
  • Conduct in-depth performance characterization and analysis on large multi-GPU and multi-node clusters.

  • Study the interaction of our libraries with all HW (GPU, CPU, Networking) and SW components in the stack

  • Evaluate proof-of-concepts, conduct trade-off analysis when multiple solutions are available

  • Triage and root-cause performance issues reported by our customers

  • Collect a lot of performance data; build tools and infrastructure to visualize and analyze the information

  • Collaborate with a very dynamic team across multiple time zones

What we need to see:
  • M.S. (or equivalent experience) or PhD in Computer Science, or related field with relevant performance engineering and HPC experience

  • 3+ yrs of experience with parallel programming and at least one communication runtime (MPI, NCCL, UCX, NVSHMEM)

  • Experience conducting performance benchmarking and triage on large scale HPC clusters

  • Good understanding of computer system architecture, HW-SW interactions and operating systems principles (aka systems software fundamentals)

  • Implement micro-benchmarks in C/C++, read and modify the code base when required

  • Ability to debug performance issues across the entire HW/SW stack. Proficient in a scripting language, preferably Python

  • Familiar with containers, cloud provisioning and scheduling tools (Kubernetes, SLURM, Ansible, Docker)

  • Adaptability and passion to learn new areas and tools. Flexibility to work and communicate effectively across different teams and timezones

Ways to stand out from the crowd:
  • Practical experience with Infiniband/Ethernet networks in areas like RDMA, topologies, congestion control

  • Experience debugging network issues in large scale deployments

  • Familiarity with CUDA programming and/or GPUs

  • Experience with Deep Learning Frameworks such PyTorch, TensorFlow

Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3, and 184,000 USD - 287,500 USD for Level 4.

You will also be eligible for equity and benefits.

Applications for this job will be accepted at least until September 13, 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.

HQ

NVIDIA Santa Clara, California, USA Office

2701 San Tomas Expressway, Santa Clara, CA, United States, Santa Clara

NVIDIA San Francisco, California, USA Office

San Francisco, United States

NVIDIA San Jose, California, USA Office

San Jose, United States

Similar Jobs

30 Seconds Ago
Easy Apply
Remote
United States
Easy Apply
26-32 Annually
Junior
26-32 Annually
Junior
Fintech • Insurance • Machine Learning • Analytics • Financial Services • Automation
Sell commercial insurance to small business customers through inbound and outbound calls. Responsibilities include qualifying prospects, setting appointments, maintaining lead systems, understanding customer needs, partnering with underwriting, presenting policies, closing deals, and building customer relationships. The role is remote within the United States and requires strong communication, coordination, adaptability, and problem-solving skills.
43 Seconds Ago
Easy Apply
Remote
United States
Easy Apply
115K-140K Annually
Senior level
115K-140K Annually
Senior level
Fintech • Insurance • Machine Learning • Analytics • Financial Services • Automation
Leads customer service operations and external vendor partnerships, including performance management, SLA and KPI tracking, forecasting, risk remediation, escalations, reporting, automation, and process improvement. Develops team members, builds operational business cases, partners with Product and Engineering, and drives scalable workflows and self-service capabilities. Requires customer service or insurance operations expertise, BPO vendor management, strong metric analysis, and P&C insurance experience.
Top Skills: Ai ToolsSpreadsheets
43 Seconds Ago
Easy Apply
Remote
United States
Easy Apply
70K-85K Annually
Mid level
70K-85K Annually
Mid level
Fintech • Insurance • Machine Learning • Analytics • Financial Services • Automation
Leads end-to-end billing and collections operations, owning bad debt recovery, litigation and settlement outcomes, vendor and BPO performance, compliance, KPIs, and allowance processes. Manages and develops collections staff, establishes procedures and service levels, partners with Accounting, Legal, Product, and Engineering, and drives automation and continuous improvement. Oversees escalations, disputes, vendor scorecards, financial close documentation, and risk-based collection strategies.
Top Skills: Google WorkspaceSalesforceSlack

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account