Senior Software Engineer – PyTorch and AI Frameworks

We are looking for experienced engineers to help build and scale next-generation AI infrastructure using PyTorch, one of the world's most widely used deep learning frameworks. This role sits at the intersection of machine learning systems, compilers, and high-performance computing, enabling researchers and product teams to train and deploy large-scale models efficiently.

You will work on core components of the PyTorch ecosystem, including model execution, distributed training, performance optimization, and developer experience.

Responsibilities:

• Design and build core PyTorch capabilities across runtime, autograd, distributed training, and model execution
• Optimize performance across GPU/accelerator backends (CUDA, Triton, etc.)
• Contribute to or lead development of large-scale ML systems and infrastructure
• Improve model training efficiency, scalability, and reliability across multi-node environments
• Work on compilers / graph transformations / kernel optimization to accelerate deep learning workloads
• Partner with researchers and applied teams to translate cutting-edge models into production systems
• Drive open-source contributions and collaborate with the broader PyTorch community
• Influence roadmap and architecture for next-gen AI platforms
• Work at the forefront of AI and accelerated computing
• Direct impact on how PyTorch runs on the world's most advanced GPU platforms
• Collaborate across hardware, systems software, and AI research to push performance boundaries and enable breakthroughs in generative AI, autonomous systems, and high-performance computing

Requirements:

• PhD or MSc degree in Computer Science, Applied Math, Physics, or related science or engineering field (or equivalent experience)
• 8+ years of software development experience
• Strong programming skills in C++ and Python
• Deep understanding of deep learning frameworks, preferably PyTorch
• Experience with GPU programming (CUDA or similar) and performance optimization

Preferred qualifications:

• Contributions to PyTorch core or ecosystem libraries
• Experience with NVIDIA AI stack (TensorRT, Triton Inference Server, cuBLAS, cuDNN, NCCL)
• Familiarity with ML compilers (TorchInductor, Triton, XLA, TVM)
• Experience optimizing LLMs or large-scale recommendation / vision models
• Background working closely with hardware-aware software optimization

Benefits:

• Competitive salaries
• Generous benefits package
• Eligible for equity

Application deadline: April 27, 2026