Jobs / United States / Nvidia Corporation

Nvidia Corporation

Senior System Software Engineer, Agentic Retrieval

5 Locations Posted today

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Skills this job asks for

LLMsRustMachine learningPythonDockerKubernetesCommunication

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Sponsorship verdict

Sponsorship possible

One solid signal, not two. Worth applying, and worth asking about sponsorship early.

  • Employer is on a government sponsor recordThe US Department of Labor certified 2,374 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first.
  • The posting doesn’t mention sponsorshipSilence isn’t a refusal — ask the recruiter before investing much time.
  • No salary bar for this routeH-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area.
  • What Nvidia Corporation paid sponsored hires in similar roles701 certified filings for “Engineer Senior Systems Software” (Software Developers) in CA: $173k–$214k, median $190k.
  • Confirmed live todayWhen a source last listed this job as open.
Details and sources
Employer is on a government sponsor record
The US Department of Labor certified 2,374 H-1B/E-3 labor condition applications for this employer between Oct 2025 and Jun 2026 (latest Jun 2026) — the step every H-1B hire needs first. Source: LCA disclosure data (US Department of Labor (OFLC)).
No salary bar for this route
H-1B has no fixed salary bar: the employer must pay at least the prevailing wage for the role and area. Cap-subject employers enter a lottery weighted by wage level. Source: https://www.federalregister.gov/documents/2025/12/29/2025-23853/weighted-selection-process-for-registrants-and-petitioners-seeking-to-file-cap-subject-h-1b, rules effective 2026-02-27.
What Nvidia Corporation paid sponsored hires in similar roles
701 certified filings for “Engineer Senior Systems Software” (Software Developers) in CA: $173k–$214k, median $190k. Most were filed at wage level IV (82%) — 4 lottery entries, ≈61% projected selection odds for cap-subject employers. Source: US Department of Labor LCA disclosure data (Oct 2025 – Jun 2026).

US H-1B: cap-subject employers enter a lottery weighted by wage level — Level I gets 1 entry, Level IV gets 4 (DHS projected selection odds ≈15% at Level I to ≈61% at Level IV). Universities and non-profit research employers are cap-exempt. The $100,000 fee for new petitions from abroad is currently blocked by a court order (appeal pending).

A verdict summarises public evidence. It is not legal advice and never a guarantee: the employer and the immigration authority decide. Sign in to factor in where you can already work.

About the role

NVIDIA's technology is at the heart of the AI revolution, touching people across the planet by powering everything from self-driving cars, robotics, co-pilots and more. Join us at the forefront of technological advancement in intelligent assistants and information retrieval. NVIDIA is looking for a System Software Engineer - Agentic Retrieval to develop pipelines for indexing and querying multi-modal content. We are looking for someone with a passion for working with the world's most challenging problems in Generative AI, LLM, VLLM, and Agentic Retrieval spaces using our innovative hardware and software platforms. You will develop tools for building powerful, flexible, multi-modal retrievers and agents driven by Large Language Models(LLM) thereby improving the experience of millions of customers. If you're creative & passionate about solving real world conversational AI problems, come join us. This role is pivotal in accelerating containerized pipelines for high quality multi-modal datasets and providing best-in-class retrieval efficacy. The day-to-day focus is on developing efficient, scalable systems for deduplicating, filtering, and classifying training corpora for tailored models that enhance off-the-shelf capabilities. Fundamental to these efforts are iterative testing and improvement in system cost, speed, & accuracy through micro-optimization, prompt engineering, fine tuning, and applying new research. The ideal candidate believes in craftsmanship whereby they release early and often to obtain feedback while keeping the long-term vision alive! They are comfortable objectively evaluating the latest AI models and frameworks with an eye towards acceleration and capability enhancement. What You'll Be Doing: • Develop and optimize Rust-based data processing frameworks, ensuring efficient handling of large datasets on GPU-accelerated environments, vital for LLM training. • Lead development and iterative optimization of components for Agentic Retrieval pipelines, ensuring they demonstrate GPU acceleration & the best performing models for improved TCO. • Collaborate with teams of LLM & ML researchers in the development of full-stack, GPU-accelerated data preparation pipelines for multimodal models Implement benchmarking, profiling, and optimization of innovative algorithms in Python in various system architectures, specifically targeting LLM applications. • Work closely with diverse teams to understand requirements, build & evaluate POCs, and develop roadmaps for production level tools and library features within the growing LLM ecosystem. • Build amazing products to improve employee productivity using Gen-AI & Co-pilot experiences! • Develop integrated systems enabling unified experience across applications and driving insights for end-to-end user experience. • Help build and maintain our Continuous Delivery pipeline with the goal of moving changes to production faster and safer, while ensuring key operational standards. • Provide peer reviews to other specialists including feedback on performance, scalability, and correctness and actively contribute to the adoption of frameworks, standards, and new technologies What We Need To See: • Bachelor’s or Master’s Degree program in Computer Science, Computer Engineering, or a related field (or equivalent experience). • 6+ years of experience in a similar or related role • Experience delivering software in a cloud context and is familiar with the patterns and process of managing cloud infrastructure • Knowledge of MLOps technologies such as Docker-Compose, Containers, Kubernetes, data center deployments etc • Excellent in-depth hands-on understanding of NLP, LLM, VLM, Generative AI, and Agentic Retrieval workflows • Self-starter with a passion for growth, enthusiasm for c

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