Senior Software Engineer, GNN

NVIDIA

. Develop accelerated, PyTorch-based solutions for large-scale machine learning models, including GNNs, TFMs, and ensemble models, with a focus on efficient training and inference on GPU infrastructure .

Posted 9/16/2026full-timeRemote • California • United StatesSenior💰 $152,000 - $287,500 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in developing and optimizing large-scale machine learning models using PyTorch and GPU infrastructure, with a strong focus on efficient training and inference workflows. Proven ability to provide technical leadership, mentor engineers, and engage with customers to drive product development and technical solutions.

Highest-signal resume keywords

PyTorch DevelopmentGPU Infrastructure OptimizationC++ ProgrammingGraph Neural Network SolutionsCustomer Engagement

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Hard Skills

Large-Scale Machine LearningDeep LearningCUDA ProgrammingModel Training and InferencePerformance OptimizationData ScienceDebugging High-Performance ApplicationsDistributed InfrastructureProfiling and Scaling WorkflowsSoftware Design

Soft Skills

CollaborationCommunicationDocumentation

Tools & Technologies

CUDA-X LibrariesPyTorch GeometricSnowflakeDatabricksFAISSMilvus

Industry Keywords

FinanceCybersecurityGovernmentNational LaboratoriesRetail

Tech Stack

Tools & technologies

Cyber SecurityPyTorchC++

About the role

Key responsibilities & impact

Develop accelerated, PyTorch-based solutions for large-scale machine learning models, including GNNs, TFMs, and ensemble models, with a focus on efficient training and inference on GPU infrastructure
Support CUDA-X Libraries and integrations used in PyTorch-based, large-scale machine learning workflows
Partner with developers, product managers, and scientists to develop innovative GNN models and GPU-accelerated implementations for model development and prediction phases
Develop solutions that help customers adopt NVIDIA hardware and software, and gather technical requirements directly from customers and Solutions Architects to guide product and engineering priorities
Provide technical leadership and mentorship to engineers across the team
Identify opportunities to improve the codebase and reduce code-maintenance overhead through re-architecture
Apply agentic coding tools to identify and fix bugs, implement new features, and refactor code
Solve complex technical issues, explain solutions clearly, exercise technical leadership, and coordinate across multiple teams to achieve shared objectives

Requirements

What you’ll need

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, including profiling, scaling, orchestration, and resource utilization
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
Experience developing or deploying Graph Neural Network solutions using PyTorch Geometric, or a similar framework
Experience working with data warehouse and lakehouse platforms, such as Snowflake or Databricks
Experience in two or more of the following domains: finance, cybersecurity, government or national laboratories, and retail
Strong understanding of system architecture, CPU, GPU, memory, and storage systems, as well as performance optimization
Experience with customer engagement and technical support, particularly for data science workflows and with vector search and storage solutions, such as FAISS or Milvus

Benefits

Comp & perks

Equity
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