About the role
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 NeMoStack services, 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 the pay of employees in similar positions. The base salary range is 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.Aplyr's read
NVIDIA is a pioneering force in GPUs and AI, attracting top talent in engineering and innovation-driven roles across various tech domains.
What's promising
- •NVIDIA leads the GPU market, crucial for gaming and AI applications.
- •The company invests heavily in AI and deep learning, driving technological advancements.
- •NVIDIA's strong market position offers stability and growth opportunities for employees.
What to watch
- •High competition in the semiconductor industry can impact market share.
- •Rapid technological changes require constant adaptation and learning.
- •Intense workload and high expectations may affect work-life balance.
Why NVIDIA
- •NVIDIA's GPUs are industry benchmarks in gaming and professional graphics.
- •The company's AI research is at the forefront of deep learning innovation.
- •NVIDIA's culture emphasizes cutting-edge technology and engineering excellence.
Aplyr’s read is generated by AI from public sources. Was it useful?
About NVIDIA
NVIDIA is a leading technology company known for its graphics processing units (GPUs) for gaming and professional markets, as well as its advancements in artificial intelligence and deep learning.
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