Machine Learning Engineer

Build on-device intelligence with NVIDIA’s GeForce G-Assist by engineering small language model (SLM) and multimodal capabilities that work reliably on-device and across hybrid cloud setups. This onsite role in Santa Clara, CA focuses on improving production behavior, grounding responses with retrieval, and enabling agentic, multi-step workflows while optimizing local inference performance.

Salary range: USD 152,000 - 287,500 per year. Your base salary will be determined based on location, experience, and compensation data for similar positions. The base salary range is 152,000 USD - 241,500 USD for Level 3 and 184,000 USD - 287,500 USD for Level 4. You may also be eligible for equity and benefits.

What you will do

• Evaluate and improve Small Language Models powering GeForce G-Assist, with a focus on accuracy, robustness, and conversational reliability.
• Identify and reduce conversation and context contamination, including state drift, prompt leakage, and retrieval cross-talk.
• Collaborate on SLM and VLM architectures to support both text and multimodal interactions.
• Develop and refine hybrid architectures that combine local SLMs with cloud-based models.
• Optimize local inference using llama.cpp, including quantization, memory usage, and performance tuning.
• Read, write, and optimize C/C++ code in performance-critical components, with proficiency in Python for supporting development.
• Design and integrate retrieval-augmented generation (RAG) to ground responses in system and user context.
• Support agentic AI workflows that enable planning, tool use, and multi-step execution.

What you bring

• 5+ years of validated experience in system software or a related field, plus an M.S. or higher in Computer Science, Data Science, Engineering, or a related field (or equivalent experience).
• Strong ability to read and write C/C++ for systems-level or performance-sensitive environments, and proficiency in Python.
• Hands-on experience with llama.cpp or similar local inference frameworks.
• Hands-on experience evaluating SLMs, including task-based and conversational testing, with an understanding of conversation dynamics, long-context behavior, and contamination challenges.
• Knowledge of SLM and VLM architectures, including trade-offs, retrieval technologies and language-model integration, and familiarity with agentic patterns such as tool use and planning.

Technologies you will work with

• C/C++, Python
• llama.cpp
• Small Language Models (SLMs)
• VLM architectures
• Retrieval-augmented generation (RAG)
• Agentic AI workflows

How to stand out

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

Additional details

• Location: Santa Clara, CA (onsite)
• Application window: at least until October 20, 2026
• This posting is for an existing vacancy.
• NVIDIA uses AI tools in its recruiting processes.