Machine Learning Engineer: AI & GPU Orchestration

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

Job summary

NVIDIA is seeking a Machine Learning Engineer to drive end-to-end lifecycle management of AI-powered systems in a finance context. The role emphasizes deploying scalable models, building AI workflows, and ensuring robust automation across distributed infrastructure.

Requirements include a PhD or Masters in a related field, 3+ years of Python experience, and strong skills with LangChain, HuggingFace, vLLM, and ML frameworks. Expect a competitive, equity-inclusive package.

Qualifications

• Master's or PhD in Computer Science, Electrical Engineering, or a related field - or equivalent experience.
• Python & Systems Engineering: 3+ years writing production-grade asynchronous Python.
• AI tools & ML Frameworks: LangChain, Hugging Face, vLLM, SGLang; TensorFlow, PyTorch, Scikit-learn.
• Data analysis: Proficient in Python data analysis using pandas/NumPy; extract insights from evaluation results.
• Deployment & Orchestration: Production-grade deployment; Kubernetes, Ray, Slurm for multi-node setups.
• GPU memory management and infrastructure tuning for high-throughput AI inference.
• GitLab CI/CD & Security: GitLab pipelines with automated tests and vulnerability scanners.
• Testing Toolchains: PyTest, mocks, and automated test generation for AI workloads.
• Advanced Git workflows: rebases, signed commits, private/public repo mirroring.

Responsibilities

• Architect, deploy, and scale open-source models using Kubernetes, Ray, or Slurm for distributed AI workloads.
• Design ML systems and data pipelines; build production-grade models and AI agents; benchmark performance.
• Run model benchmarks and perform error analyses; build dashboards to communicate results to stakeholders.
• Take ownership of features from ideation to production, coordinating updates across code repositories.

Skills

Python

Data analysis

CI/CD

Git workflows

Testing automation

GPU optimization

Distributed systems

Education

Master's or PhD in Computer Science or Electrical Engineering

Tools

LangChain

HuggingFace

vLLM

SGLang

TensorFlow

PyTorch

Scikit-learn

Kubernetes

Ray

Slurm

Pandas

NumPy

GitLab

PyTest

Job description

NVIDIA is seeking a Machine Learning Engineer to drive end-to-end lifecycle management of AI-powered systems in a finance context. The role emphasizes deploying scalable models, building AI workflows, and ensuring robust automation across distributed infrastructure.

Requirements include a PhD or Masters in a related field, 3+ years of Python experience, and strong skills with LangChain, HuggingFace, vLLM, and ML frameworks. Expect a competitive, equity-inclusive package.