Senior System Software Engineer, Agentic Retrieval

Nvidia

Confirmed live today High trust
Remote

Quick summary

Work type
Remote
Location
Santa Clara, CARedmond, WA
Salary
$184,000–$287,500 / yr
Employment
Full-time
Posted
2 days ago
Freshness
Confirmed live today

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $199k
This role $236k
$136k most similar roles pay here $304k

This role pays more than 82% of similar roles. Most pay $163,175–$235,750 — the shaded band above. At the midpoint, this role pays about $236k versus about $199k for comparable roles.

Based on 240 similar postings.

Employer

About Nvidia

Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing

Nvidia currently has 1391 open roles on FindRole.

Listed pay typically runs $184,000–$287,500 across 1116 roles with salary data.

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At a glance

TL;DR · Senior System Software Engineer, Agentic Retrieval

As a Senior System Software Engineer, Agentic Retrieval, you will join the team to develop pipelines for indexing and querying multi-modal content. You will build tools for creating flexible, multi-modal retrievers and agents driven by Large Language Models while accelerating containerized pipelines for high-quality datasets. Your daily responsibilities include developing Rust-based data processing frameworks for GPU-accelerated environments, implementing Python-based benchmarking and profiling of algorithms, and performing micro-optimization, prompt engineering, and fine-tuning to improve system cost and accuracy. You will work on deduplicating, filtering, and classifying training corpora for tailored models. The role requires expertise in NLP, LLM, VLM, and Agentic Retrieval workflows, alongside proficiency with MLOps technologies like Docker-Compose and Kubernetes. This position focuses on solving complex problems in Generative AI to improve retrieval efficacy and provide high-quality multi-modal data preparation.

What you'll do

  • Develop and optimize Rust-based data processing frameworks for large datasets in GPU-accelerated environments.
  • Build and optimize Agentic Retrieval pipelines to improve retrieval efficacy and total cost of ownership.
  • Create full-stack, GPU-accelerated data preparation pipelines for multi-modal models.
  • Benchmark, profile, and optimize innovative algorithms in Python across various system architectures.
  • Develop systems for deduplicating, filtering, and classifying training corpora for tailored LLM models.
  • Perform micro-optimization, prompt engineering, and fine-tuning to improve system cost, speed, and accuracy.
  • Build and maintain continuous delivery pipelines to move changes to production faster and safer.
  • Evaluate the latest AI models and frameworks to identify opportunities for acceleration and capability enhancement.

What we're looking for

  • Bachelor's or Master's degree 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 familiarity with managing cloud infrastructure.
  • Knowledge of MLOps technologies including Docker-Compose, Containers, Kubernetes, and data center deployments.
  • In-depth hands-on understanding of NLP, LLM, VLM, Generative AI, and Agentic Retrieval workflows.
  • Proficiency in developing Rust-based data processing frameworks for GPU-accelerated environments.
  • Ability to perform benchmarking, profiling, and optimization of algorithms in Python across various system architectures.
  • Excellent communication skills to distill sophisticated topics into understandable conclusions for multi-functional teams.

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