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NVIDIA

Designs the chips and software that power AI

Machine Learning Engineer - GeForce G-Assist

Natural Language Processing & LLMsConfirmed live in the last 24 hours
Full-timeIn-person

About the Job

Requirements

  • At least 5 years of validated experience in system software or a related field, with an M.S. or higher degree in Computer Science, Data Science, Engineering, or a related field, or equivalent experience.
  • Ability to read and write C/C++ code in systems-level or performance-sensitive environments, proficiency in Python, and hands-on experience with llama.cpp or similar local inference frameworks.
  • Hands-on experience evaluating Small Language Models, including task-based and conversational testing, and understanding conversation dynamics, long-context behavior, and contamination challenges.
  • Knowledge of Small Language Model and Vision Language Model architectures and their trade-offs, experience with retrieval technologies and language-model integration, and familiarity with agentic AI patterns such as tool use and planning.

Responsibilities

  • Evaluate and improve Small Language Models used in GeForce G-Assist, emphasizing accuracy, robustness, and conversational reliability.
  • Identify and mitigate conversation and context contamination, including state drift, prompt leakage, and retrieval cross-talk.
  • Work with Small Language Model and Vision Language Model architectures to support text and multimodal interactions.
  • Collaborate on hybrid architectures that combine local Small Language Models with cloud-based models, considering model behavior and runtime performance.
  • Optimize local inference using llama.cpp, including quantization, memory usage, and performance tuning.
  • Read, write, and optimize C/C++ code in performance-critical paths.
  • Design and integrate retrieval-augmented generation systems that ground responses in system and user context.
  • Support agentic AI workflows that enable planning, tool use, and multi-step execution.

Desired Qualifications

  • Experience contributing to language or multimodal models that power user-facing products, features, or workflows.
  • A track record of collaborating with product, platform, or systems teams to balance model capability, performance, and user experience.
  • Ability to translate user needs or feedback into measurable improvements in model behavior or system reliability.

About the Company

NVIDIA

Designs the chips and software that power AI

NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.

Company size
10,001+
Company stage
IPO
Headquarters
Santa Clara, CA
Founded
1993

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