Senior ML Systems Engineer — GPU-Accelerated PyTorch & GNNs

NVIDIA AI; Austin (CA); On-site; USD 140,000 - 190,000; Full time

Benefits offered by this job

Equity

Benefits

Job summary

NVIDIA AI in Austin is seeking an experienced ML engineering professional to develop and optimize accelerated PyTorch-based solutions for large-scale models on GPU infrastructure.

You will collaborate with cross-functional teams, support CUDA-X libraries, and influence product priorities based on customer technical requirements. A strong background in C++, PyTorch, and GPU-accelerated development is essential.

Qualifications

• Requires a Bachelor's degree with 5+ years of experience or a Master's/PhD with 3+ years in machine learning and data science.
• Strong C++ skills, extensive experience with PyTorch, and a proven track record in GPU-accelerated application development.

Responsibilities

• Develop and optimize accelerated PyTorch-based solutions for large-scale ML models on GPU infrastructure.
• Collaborate with cross-functional teams to support CUDA-X libraries and guide product priorities based on customer technical requirements.

Skills

PyTorch

C++

CUDA

Graph Neural Networks

Machine Learning

Deep Learning

GPU Acceleration

Distributed Infrastructure

Data Science

Performance Optimization

Software Design

System Architecture

PyTorch Geometric

Profiling

Orchestration

Education

Bachelor's degree

Master's degree

PhD

Job description

NVIDIA AI in Austin is seeking an experienced ML engineering professional to develop and optimize accelerated PyTorch-based solutions for large-scale models on GPU infrastructure.

You will collaborate with cross-functional teams, support CUDA-X libraries, and influence product priorities based on customer technical requirements. A strong background in C++, PyTorch, and GPU-accelerated development is essential.