System Software Engineer – RAG

NVIDIA

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 Python-based data processing frameworks, ensuring efficient handling of large datasets on GPU-accelerated environments, vital for LLM training.
  • Contribute to the design and implementation of RAPIDS and other GPU-accelerated libraries, focusing on seamless integration and performance enhancement in the context of LLM training data preparation and RAG pipelines.
  • Lead development and iterative optimization of components for RAG 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 complementary 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!
  • Collaborate with your peers to craft, develop, test, and maintain integrated applications and features.
  • 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.
  • 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 demonstrated experience in a similar or related role
  • Experience delivering software in a cloud context and is familiar with the patterns and process of handling 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, MLLM, Generative AI , and RAG workflows
  • Self-starter with a passion for growth, enthusiasm for continuous learning and sharing findings across the team
  • Extremely motivated, highly passionate, and curious about new technologies.
  • 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.
  • Comfortable working in a fast-paced, highly collaborative environment

Ways To Stand Out Of The Crowd:

  • Experience working with multiple languages, chunking, data pre-processing and model fine-tuning
  • Demonstrated attention to detail and ability to spot patterns in sophisticated data
  • Active engagement (published papers, conference talks, blogs) in the data science community
  • Experience building applications using Generative AI , LLMs, RAGs & Copilots for enterprise.

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