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Pytorch Jobs (NOW HIRING)

PyTorch Role/C++,Python Role Job Location: Bellevue, WA Job Type: Full time * 10+ years of experience in systems/software engineering or HPC/AI development * Strong programming expertise in Python ...

PyTorch Expert Type: Contract Compensation: $70-$110/hour Location: Remote Commitment: 40 hours/week Role Responsibilities * Guide research and engineering teams to close knowledge gaps and improve ...

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Pytorch information

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$80.5K

$144.3K

$207K

How much do pytorch jobs pay per year?

As of Jul 18, 2026, the average yearly pay for pytorch in the United States is $144,320.00, according to ZipRecruiter salary data. Most workers in this role earn between $103,000.00 and $176,500.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Pytorch position, and why are they important?

To thrive in a PyTorch developer role, you need a strong background in deep learning, programming (especially Python), and a solid understanding of machine learning fundamentals, often supported by a degree in computer science, engineering, or a related field. Experience with PyTorch, CUDA, cloud platforms (like AWS or Azure), and familiarity with data processing pipelines are highly valued, and certifications in AI or machine learning can be beneficial. Key soft skills include problem-solving, teamwork, and effective communication to collaborate with cross-functional teams and present technical results clearly. These skills are crucial for building robust machine learning models, ensuring reproducibility, and driving innovation in fast-paced, data-driven environments.

What kinds of projects or tasks can a PyTorch developer expect to work on in a typical role?

As a PyTorch developer, you will likely work on developing, refining, and deploying deep learning models for tasks such as image recognition, natural language processing, or recommendation systems, depending on your company's focus. Your responsibilities may include data preprocessing, model architecture design, experimentation, performance tuning, and collaborating with data scientists and software engineers to integrate models into production systems. You might also be called upon to conduct research or prototype new algorithms, keeping up with the latest advancements in the AI field. Projects can vary from quick proofs of concept to large-scale deployments, offering diverse opportunities to grow your technical and collaborative skills.

What is a PyTorch job?

A PyTorch job typically involves working with the PyTorch deep learning framework to develop, train, and deploy machine learning models. Professionals in this role may build neural networks, perform data preprocessing, optimize models, and integrate them into applications. These jobs are commonly found in AI research, software development, and data science, requiring expertise in Python, deep learning, and model optimization techniques.

More about Pytorch jobs
What cities are hiring for Pytorch jobs? Cities with the most Pytorch job openings:
What are the most commonly searched types of Pytorch jobs? The most popular types of Pytorch jobs are:
What states have the most Pytorch jobs? States with the most job openings for Pytorch jobs include:
Infographic showing various Pytorch job openings in the United States as of July 2026, with employment types broken down into 18% Internship, and 82% Full Time. Highlights an 82% In-person, and 18% Remote job distribution, with an average salary of $144,320 per year, or $69.4 per hour.
PyTorch Role/C++,Python

PyTorch Role/C++,Python

Staffingine LLC

Bellevue, WA • On-site

Full-time

Re-posted 6 days ago


Job description

Job Title: PyTorch Role/C++,Python Role
Job Location: Bellevue, WA
Job Type: Full time

Job Description:

  1. 10+ years of experience in systems/software engineering or HPC/AI development  
  2. Strong programming expertise in Python and low-level programming (C/C++ preferred)
  3. Deep understanding of:
  4. GPU accelerator architectures
  5. Parallel computing models
  6. Memory and compute optimization
  7. Experience with:
  8. PyTorch (model-level workloads and execution)
  9. Triton (custom kernel development / compiler-level interaction)
  10. Distributed computing frameworks (MPI, NCCL, etc.)
  11. Strong knowledge of:
  12. Compiler stacks / SDK architecture
  13. Runtime systems and execution pipelines