ML Engineer: AI Systems & Distributed Deployment

NVIDIA; California (MO); On-site; USD 152,000 - 242,000; Full time

Job summary

NVIDIA is seeking a talented Machine Learning Engineer to lead end-to-end AI system development, deployment, and automation. You will architect scalable models, build AI workflows with Kubernetes, Ray, and Slurm, and implement secure CI/CD pipelines with GitLab.

Expect ownership from ideation to production and cross-team collaboration on high-performance GPU workloads. The role requires a Master’s or PhD in a related field, 3+ years of Python experience, and deep expertise with LangChain,

Qualifications

• Master's or PhD in Computer Science, Electrical Engineering, or related field, or equivalent experience.
• 3+ years of professional experience writing production-grade, asynchronous Python and robust system design.
• Deep experience with LangChain, Hugging Face libraries, vLLM, and SGLang; TensorFlow, PyTorch and Scikit-learn.
• Proficient in data analysis using Python (pandas, NumPy) and communicating results to technical and non-technical audiences.
• Production-grade model deployment, monitoring, and multi-node scaling with Kubernetes, Ray, or Slurm.
• Strong understanding of GPU memory management and infrastructure tuning for high-throughput AI inference.
• GitLab CI/CD and security automation integrated into MR workflows.
• Familiarity with PyTest, mocking, and automated test generation for AI workloads.
• Advanced Git workflows, including rebase strategies and signed commits.

Responsibilities

• Architect, deploy, and scale open-source models using Kubernetes, Ray, or Slurm for robust AI workloads.
• Design experiments, prompt-tune, evaluate, and deploy production-grade models and AI agents with scalable data pipelines.
• Run model benchmarks, perform error analysis, and build dashboards to communicate performance to stakeholders.
• Take ownership of features from ideation to production across multiple repositories and teams.

Skills

Python

Data analysis

CI/CD automation

Git workflows

Testing frameworks

Distributed AI systems

Education

Master's degree in CS/EE or related

PhD in CS/EE or related

Tools

Kubernetes

Ray

Slurm

LangChain

Hugging Face

vLLM

SGLang

TensorFlow

PyTorch

Scikit-learn

GitLab

PyTest

Job description

NVIDIA is seeking a talented Machine Learning Engineer to lead end-to-end AI system development, deployment, and automation. You will architect scalable models, build AI workflows with Kubernetes, Ray, and Slurm, and implement secure CI/CD pipelines with GitLab.

Expect ownership from ideation to production and cross-team collaboration on high-performance GPU workloads. The role requires a Master’s or PhD in a related field, 3+ years of Python experience, and deep expertise with LangChain,