Senior System Software Engineer, Agentic Retrieval

NVIDIA•Redmond, CA

About The Position

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.

Requirements

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 continuous learning and sharing findings across the team
Outstanding communication skills for distilling sophisticated topics down to understandable, impactful conclusions.
Ability to work successfully with multi-functional teams, principals, and architects.
Coordinates optimally across organizational boundaries and geographies.

Responsibilities

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