Senior Software Engineer

🕒 June 4

🏄 California, Colorado, +3 more states – Remote

🏄 California – Remote ⛰️ Colorado – Remote 🗽 New York – Remote 🍂 Massachusetts – Remote ☕ Washington – Remote

💵 $184k - $356.5k / year

⏰ Full Time

🟠 Senior

🧑‍💻 Full-stack Engineer

🦅 H1B Visa Sponsor

This company has sponsored H1B visas in the past.

👻 Ghost score 46%

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NVIDIA

WebsiteLinkedInAll Job Openings

10,000+ employees

Founded 1993

🏥 Healthcare

🏭 Manufacturing

🤖 Artificial Intelligence

Healthcare • Manufacturing • Artificial Intelligence

NVIDIA is a leading technology company specializing in accelerated computing and artificial intelligence. NVIDIA pioneers advancements in graphical processing units (GPUs), cloud computing, data centers, and virtual reality, with a focus on gaming, automotive, healthcare, and robotics industries. The company's innovations, such as NVIDIA Omniverse, transform traditional digital processes by enabling high-fidelity simulations and rendering tasks. Their applications span various industries, from autonomous vehicles using NVIDIA DRIVE to healthcare solutions with NVIDIA Clara, and AI-driven analytics and workflows.

📋 Description

• 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 across NVIDIA agent runtimes and developer workflows • 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 test coverage across unit, integration, E2E, Docker, and Kubernetes workflows • Drive 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

🎯 Requirements

• 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 • 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

🏖️ Benefits

• Equity • Benefits

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