Senior AI Platform Engineer — NIM Tools (Equity)

Nvidia Corporation in; Santa Clara (CA); On-site; USD 184,000 - 357,000; Full time

Job summary

NVIDIA in Santa Clara, CA is hiring a Senior Software Engineer for the NIM Tools (Finance) team to build a groundbreaking model customization and deployment lifecycle platform.

You will define the product surface used by ISVs and CSPs worldwide, enabling models from selection through fine-tuning, evaluation, deployment, and compliance with strong emphasis on APIs, observability, and scalable infrastructure.

Qualifications

• Bachelor's degree in Computer Science, Engineering, or equivalent experience.
• 7+ years of experience with LLM serving infrastructure (vLLM, TRT-LLM, or equivalent).
• Deep understanding of model quantization and fine-tuning workflows.
• Demonstrated history of developing robust platform APIs.
• Strong collaborative skills and experience working in cross-functional teams.
• Outstanding problem-solving skills and meticulous attention to detail.

Responsibilities

• Compose and build the fine-tuning handoff pipeline, including LoRA adapter repackaging, re-quantization, and re-validation into NIM.
• Develop the evaluation harness, ensuring models meet our high standards.
• Implement the observability and attestation layer to produce auditable compliance artifacts.
• Work with ISVs and CSPs to roll out NVIDIA NIMs at scale.
• Define and improve durable platform APIs, avoiding one-off integrations.
• Ensure flawless project completion with rigorous methodologies.

Skills

LLM serving infra

Quantization & fine-tuning

API design & dev

Collaborative work

Problem solving

Education

Bachelor's degree in Computer Science, Engineering, or equivalent

Tools

vLLM

TRT-LLM

Job description

NVIDIA in Santa Clara, CA is hiring a Senior Software Engineer for the NIM Tools (Finance) team to build a groundbreaking model customization and deployment lifecycle platform.

You will define the product surface used by ISVs and CSPs worldwide, enabling models from selection through fine-tuning, evaluation, deployment, and compliance with strong emphasis on APIs, observability, and scalable infrastructure.