Software Engineer, Technical Lead – Data Platform

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.

• 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.

• 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.

• 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…