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Job Description: Senior Software Engineer - PyTorch
OpenTeams · United States (Remote)

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About the job
Senior Software Engineer: Numerical and High Performance Computing (Python/C++)

Location: Remote - U.S
Duration: Full-Time


The base salary range for this role is $130,000 – $200,000 USD, depending on experience, skills, role level, and geographic location. In addition to base salary, this role may be eligible for equity, bonuses, and a comprehensive benefits package



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.


What You’ll Do

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, Numba, 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


What We’re Looking For

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