NVIDIA is looking for a Senior Software Engineer to develop large-scale machine learning solutions, focusing on PyTorch-based frameworks and GPU acceleration. The role involves working on advanced models like Graph Neural Networks and Tabular Foundation Models. The team aims to enhance training and inference workflows for machine learning models on NVIDIA's GPU infrastructure. This position offers the chance to contribute to cutting-edge data science solutions and support customer engagement.

• Bachelor's degree or equivalent experience plus 5 or more years of relevant experience in large-scale machine learning, deep learning, and general data science, or a Master's degree or PhD plus 3 or more years of relevant experience.
• 3 or more years of experience with PyTorch.
• 2 or more years of experience training enterprise-scale machine learning models across distributed infrastructure.
• 2 or more years of experience designing and operating efficient training and inference workflows on GPU infrastructure.
• Excellent C++ programming and software design skills.
• Proven experience developing, debugging, and optimizing high-performance applications, preferably with GPU acceleration using CUDA.
• Strong collaboration, communication, and documentation habits.

• Develop accelerated, PyTorch-based solutions for large-scale machine learning models.
• Support CUDA-X Libraries and integrations used in PyTorch-based workflows.
• Partner with developers, product managers, and scientists to develop innovative GNN models.
• Gather technical requirements directly from customers and Solutions Architects.
• Provide technical leadership and mentorship to engineers across the team.
• Identify opportunities to improve the codebase and reduce code-maintenance overhead.
• Apply coding tools to identify and fix bugs, implement new features, and refactor code.
• Solve complex technical issues and coordinate across multiple teams.

• Employees at NVIDIA are often offered comprehensive, day-one benefits—including medical, dental, and vision coverage with HSA support, life and disability insurance, an Employee Assistance Program, and a 401(k) with auto-enrollment. Many roles also have generous time off and holidays, donation matching (up to $10,000), and a wide menu of extras like FSAs, commuter benefits, legal and identity-theft protection, pet insurance, and wellness discounts. Optional programs can include student-loan and home-purchase support, plus family care resources and expert medical services.