ML Engineer - Scalable AI Systems & GPU Orchestration

NVIDIA; Santa Clara (CA); On-site; USD 152,000 - 242,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA is seeking a talented Machine Learning Engineer to drive end-to-end AI system development, evaluation, deployment and lifecycle management. You will deploy and scale models across distributed infrastructure, manage GPU orchestration, prompt-tune models, and build advanced AI workflows using Kubernetes, Ray, or Slurm.

You will work on designing experiments, benchmarking, and building testing frameworks within secure CI/CD pipelines with GitLab, ensuring code quality and system resilience.

Qualifications

• Master’s or PhD in CS/EE or equivalent
• 3+ years of production-grade Python experience
• Experience with LangChain and ML frameworks (TF/PyTorch/Scikit-learn)
• Data analysis in Python (pandas/NumPy)
• Production-grade model deployment and monitoring
• CI/CD with GitLab and security automation
• Advanced Git workflows and collaboration
• GPU memory management for high-throughput AI inference
• Container orchestration with Kubernetes
• Benchmarking, analytics dashboards for stakeholders

Responsibilities

• Architect, deploy, and scale AI models with Kubernetes, Ray, or Slurm
• Design ML systems and data pipelines; prompt-tune and deploy production models
• Run model benchmarks and build analytics dashboards for stakeholders
• Own features from ideation to production across repos

Skills

Python development

Asynchronous Python

GitLab CI/CD

PyTest

Data analysis Python

Education

Master's/PhD in CS/EE

Tools

Kubernetes

Ray

Slurm

LangChain

Hugging Face

vLLM

SGLang

TensorFlow

PyTorch

Scikit-learn

Job description

NVIDIA is seeking a talented Machine Learning Engineer to drive end-to-end AI system development, evaluation, deployment and lifecycle management. You will deploy and scale models across distributed infrastructure, manage GPU orchestration, prompt-tune models, and build advanced AI workflows using Kubernetes, Ray, or Slurm.

You will work on designing experiments, benchmarking, and building testing frameworks within secure CI/CD pipelines with GitLab, ensuring code quality and system resilience.