Software Engineer, Technical Lead – Performance Data Platform
NVIDIA is hiring a Software Engineer, Technical Lead – Performance Data Platform in Santa Clara, United States. It pays $272k-$431k a year and Level rates it ; you can apply on NVIDIA.
Level's read on this job
- On Level's scale, this software engineer role is Works on AI ●●●○: the daily work is on AI products, without building the model.
- Pay on this posting starts 63% higher than the typical software engineer posting on Level.
- The posting mentions system architecture, distributed systems and data platforms among its tools and skills.
- NVIDIA has 2,600+ other open roles on Level.
- Posted within the past week.
AI in this role
Lead the architecture of a data center scale performance data platform supporting AI workloads and automated analysis agents.
NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in an inclusive, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world.
NVIDIA wants a technical lead to invent a new platform that enables engineers to assess the performance of AI workloads running on numerous computing nodes. Our team develops software tools for technical users to comprehend complex computing systems. You will lead the architecture of a system that collects performance data at a data center scale, maintains it as searchable history, and permits both people and automated analysis agents to find and explain performance issues. You will evolve this from an early prototype into a product used by other teams, while building hands-on as the team expands.
What you’ll be doing:
- Define the end-to-end architecture: the data model, the service and API contracts, and the boundaries with the tools and teams that produce the data.
- Make foundational decisions and justify them in documents. Include considered alternatives and evidence that could reverse them. Align these decisions with partner teams and their roadmaps.
- Build in the early phase: stand up services, APIs and a deployment path yourself, so that partners can develop the system before every role is filled.
- Explain how automated analysis agents operate within the platform. Describe what queries they may perform, how their results relate to evidence, and the constraints on their cost and response time.
- Review performance diagnoses and drive the first use cases with design partners, mentor engineers, and establish the engineering approaches the team grows into.
What we need to see:
- Bachelor’s degree in Computer Science, Computer Engineering, or a related field, or equivalent experience.
- 15+ years of software engineering experience, including technical leadership of a data-intensive platform that shipped end to end and was used by other teams.
- Experience developing or managing systems where automated agents or models process large amounts of production data, including methods used to assess the quality of their results.
- Practical knowledge of GPU and machine learning workload performance: you can review a performance diagnosis, question its evidence, and decide which signals matter most.
- A track record of crafting APIs and data models that evolved without breaking existing users or deployments.
- Hands-on ability to build and deploy services and tooling yourself, including when using automated development tools, and to verify the result independently through tests and measurements.
- Clear communication of build choices, trade-offs and uncertainty to engineers, partner teams and leadership, and the ability to align teams without direct authority.
- Proficiency with C++, Go, Python.
Ways to stand out from the crowd:
- Background in developer tools, profilers or performance-analysis products.
- Experience transforming a prototype into a platform embraced by multiple teams with distinct priorities.
- Identity, access control and multi-tenant build for products that hold customers’ data.
- Evaluation approach for the output of analysis agents or models: labeled cases, precision and recall, abstention.
- Working knowledge of SQL and TypeScript.
Join NVIDIA and be part of a team that’s redefining what’s possible through technology. Together, we’ll build a platform that sets new standards for performance data analysis and empowers engineers worldwide to achieve flawless results!
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 272,000 USD – 431,250 USD.You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 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.How we rate this
Software Engineer, Technical Lead – Performance Data Platform at NVIDIA rates 65 out of 100 for how much of the daily work is AI. That makes it Works on AI (AI Level 3 of 4). The level is about AI in the job, not seniority.
Works on AI. The daily work is on AI products, without building the model.
- ●●●● Builds AI80 to 100
- ●●●○ Works on AI60 to 79
- ●●○○ Uses AI40 to 59
- ●○○○ Little AI0 to 39
Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.
Prepare for this job
Built from this posting and from similar jobs on Level.
Skills and AI tools this role asks for
Pay
- This job starts at
- $272k
- Typical software engineer job
- $167k
This posting starts 63% above the typical software engineer job. See software engineer jobs
Questions you could be asked
- Tell me about a project where system architecture was part of your work. What did you do?
- Tell me about a project where distributed systems was part of your work. What did you do?
- Tell me about a project where data platforms was part of your work. What did you do?
- Tell me about a project where technical leadership was part of your work. What did you do?
- Tell me about a project where performance monitoring was part of your work. What did you do?
Adapt your resume
- List these exact terms on your resume: System Architecture, Distributed Systems, Data Platforms, Technical Leadership, and Performance Monitoring. An applicant tracking system matches the wording, not the idea.
- Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
- Show where AI is part of your daily process, not a one-off project. This role expects it to be a running habit.
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