We are looking for a Senior Software Engineer to help build NeMo Platform, NVIDIA’s product for developing, evaluating, deploying, and operating AI systems at scale. This role will focus on NeMo Evaluator, which helps teams understand whether changes to AI agents are making those agents better. As AI systems become more autonomous and more deeply integrated into real workflows, teams need practical infrastructure for observing behavior, measuring progress, catching regressions, and iterating with confidence.
Our roadmap is increasingly focused on agentic development and automated agent improvement: giving teams the infrastructure they need to compare versions, understand behavior, and make empirically grounded improvements over time.
What you'll be doing:
Design and implement Python-first APIs, SDK workflows, and plugin interfaces for building, measuring, and improving agents across multiple runtimes and product surfaces
Build reusable systems for observing behavior, measuring progress, detecting regressions, and turning runtime evidence into product decisions
Build systems for ingesting, normalizing, validating, and analyzing agent execution data and evaluation datasets
Partner with research, product, platform, and infrastructure teams to integrate agentic capabilities broadly across NVIDIA agent runtimes and developer workflows
Help turn emerging agent development and improvement techniques into reliable, reusable product capabilities
Improve reliability, observability, debuggability, and performance across NeMo Platform, SDKs, plugins, jobs, and developer workflows
Build strong test coverage across unit, integration, E2E, Docker, and Kubernetes workflows
Drive “speed of light” engineering: fast iteration, high ownership, pragmatic decisions, and performance-minded implementation under production constraints
Provide senior technical leadership through design reviews, code reviews, mentoring, and ownership of ambiguous cross-component problems
What we need to see:
BS, MS, or equivalent experience in Computer Science, Computer Engineering, or a related technical field
5+ years of professional software engineering experience building production systems
Excellent Python engineering skills, including API design, typing, testing, debugging, performance analysis, and maintainable software design
Experience designing SDKs, libraries, plugins, CLIs, or other developer-facing interfaces
Experience with distributed systems, cloud-native services, containers, Kubernetes, or job orchestration
Strong understanding of reliability, scalability, security, and performance tradeoffs in production infrastructure
Experience with structured data modeling and validation systems such as Pydantic, typed schemas, event/trace models, or SDK-generated types
Ability to work independently, define technical scope, break down ambiguous problems, and drive work across team boundaries
Clear communication skills and a track record of collaborating with engineering, product, research, or customer-facing teams
Ways to stand out from the crowd:
Experience building, deploying, and iterating on production agentic AI systems where evaluation was used to measure and improve real product outcomes
Experience designing evaluation workflows for heterogeneous agents, including tool-using agents, RAG agents, workflow agents, coding agents, or long-running autonomous systems
Experience integrating evaluation capabilities across multiple products, runtimes, or internal platforms, especially through Python SDKs, plugins, or shared developer tooling
Strong ability to connect technical evaluation work to business outcomes, product quality, user experience, reliability, or operational efficiency
Experience with enterprise AI systems where measurement, regression testing, observability, governance, and continuous improvement are required for production deployment
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you’re passionate about leading breakthrough AI research and building exceptional teams that shape the future of computing, we want to hear from you.
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary ranges for this position are:184,000 USD – 287,500 USD for Level 4; and 224,000 USD – 356,500 USD for Level 5.
You will also be eligible for equity and benefits.
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.Skills Required
- BS, MS, or equivalent experience in Computer Science, Computer Engineering, or a related technical field
- 5+ years of professional software engineering experience building production systems
- Excellent Python engineering skills, including API design, typing, testing, debugging, performance analysis, and maintainable software design
- Experience designing SDKs, libraries, plugins, CLIs, or other developer-facing interfaces
- Experience with distributed systems, cloud-native services, containers, Kubernetes, or job orchestration
- Strong understanding of reliability, scalability, security, and performance tradeoffs in production infrastructure
- Experience with structured data modeling and validation systems such as Pydantic, typed schemas, event or trace models, or SDK-generated types
- Ability to work independently, define technical scope, break down ambiguous problems, and drive work across team boundaries
- Clear communication skills and a track record of collaborating with engineering, product, research, or customer-facing teams
- Experience building, deploying, and iterating on production agentic AI systems where evaluation measured and improved product outcomes
- Experience designing evaluation workflows for heterogeneous agents, including tool-using, RAG, workflow, coding, or long-running autonomous agents
- Experience integrating evaluation capabilities across multiple products, runtimes, or internal platforms through Python SDKs, plugins, or shared developer tooling
- Ability to connect technical evaluation work to business outcomes, product quality, user experience, reliability, or operational efficiency
- Experience with enterprise AI systems requiring measurement, regression testing, observability, governance, and continuous improvement for production deployment
NVIDIA Compensation & Benefits Highlights
The following summarizes recurring compensation and benefits themes identified from responses generated by popular LLMs to common candidate questions about NVIDIA and has not been reviewed or approved by NVIDIA.
-
Equity Value & Accessibility — Feedback suggests equity grants, stock options/RSUs, and a discounted ESPP materially boost total compensation and can deliver significant wealth-building when the stock performs well.
-
Healthcare Strength — Feedback suggests medical, dental, and vision plans with in-network preventive care at 100%, telehealth, and concierge-style support are comprehensive and valued.
-
Parental & Family Support — Feedback suggests up to 22 weeks fully paid parental leave, fertility coverage, and adoption/surrogacy reimbursement provide strong family-focused benefits.
NVIDIA Insights
What We Do
NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, NVIDIA is increasingly known as “the AI computing company.”
