Senior Software Engineer: Numerical and High Performance Computing

We’re looking for a highly motivated Software Engineer with a strong background in numerical computing, high-performance computing (HPC), or deep learning frameworks to join our PyTorch-focused engineering team. If you’re passionate about building performant systems, contributing to open source, and shaping the future of the Python AI ecosystem, this role is for you.

Have you seen the explosive growth of Python in data science and machine learning? Are you excited by the impact of tools like PyTorch, NumPy, Triton, and Dask? In this role, you’ll help advance that ecosystem by building features and performance improvements used by millions.

You will:

• Develop, optimize, and maintain core components of PyTorch and related open-source libraries
• Contribute directly to projects such as PyTorch, TorchRL, TorchAO, and Triton
• Work across C++, CUDA, Python, C, and MLIR
• Design and implement new features, performance enhancements, kernel optimizations, and infrastructure improvements
• Debug complex numerical, performance, and scalability issues in large, production-level codebases
• Engage with the broader PyTorch community, including maintainers, contributors, and users
• Collaborate closely with internal engineering teams and client partners using PyTorch at scale
• Participate in code reviews, architectural discussions, and team mentoring
• Build your presence and impact within the Python and open-source communities

You don’t need to be an expert in every PyTorch submodule — we care about strong fundamentals and the ability to learn quickly. If you have experience with large-scale systems and modern numerical or GPU computing, you’ll thrive here.

Strong candidates will have experience with:

• C++ and Python in production environments
• GPU programming (CUDA preferred)
• High-performance or numerical computing
• Working in large, complex codebases
• Debugging low-level or performance-critical issues
• Communicating clearly within engineering teams and open-source communities

Bonus experience (nice to have, not required):

• PyTorch, NumPy, or other scientific Python libraries
• Deep learning fundamentals or experience with training/inference systems
• MLIR, Triton, or compiler-related tooling

We invest heavily in helping engineers grow within both OpenTeams and the Python open-source ecosystem. If you’re excited about advancing open-source AI infrastructure and collaborating with world-class maintainers, we’d love to talk.