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Pytorch Developer Jobs in Seattle, WA (NOW HIRING)

VeridianTech

Python Automation Developer (Onsite)

Seattle, WA · On-site

$57.25 - $78.75/hr

Hi, Job Title: - Python Automation Developer Location: - Renton, WA / Everett, WA Full-time ... TensorFlow and PyTorch; 4. Framework: Django ; Flask; FastAPI 5. Web Scraping and HTTP: Beautiful ...

Nvidia

Senior Software Engineer, AI Networking

Seattle, WA · On-site

$139K - $183K/yr

Knowledge in PyTorch, CUDA, and NCCL libraries. * Proven software engineering/development skills ... With competitive salaries and a comprehensive benefits package, NVIDIA is widely regarded as one of ...

General Robotics

Systems Engineer

Redmond, WA · On-site

They are seeking a Systems Engineer to optimize infrastructure for robotics workloads, focusing on ... PyTorch, JAX, TensorFlow) for robotics applications. • Build and maintain containerized ...

Team Red Dog

AI Robotics Engineer

Redmond, WA · On-site

In this hands-on engineering role, you'll develop machine learning pipelines, integrate robotic ... PyTorch (2+ years) - Train, fine-tune, evaluate, and optimize robotics foundation models, vision ...

Team Red Dog

AI Robotics Engineer

Redmond, WA · On-site

In this hands-on engineering role, you'll develop machine learning pipelines, integrate robotic ... PyTorch (2+ years) - Train, fine-tune, evaluate, and optimize robotics foundation models, vision ...

General Robotics

Systems Engineer

Redmond, WA · On-site

$155K - $205K/yr

Optimize GPU/CUDA workloads and accelerate ML frameworks (PyTorch, JAX, TensorFlow) for robotics ... Strong systems programming skills in one or more of: C++, Rust, Go, Python. * Solid understanding ...

Zortech Solutions

MLOps Engineer

Bellevue, WA · Remote

Job Title MLOps Engineer to work on AWS GovCloud Databricks Projected Start Date05-09-2025 ... PyTorch, HuggingFace Transformers and libraries (like scikit-learn, etc.). * 4-6 years of ...

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Pytorch Developer information

What is a PyTorch developer?

A PyTorch Developer is a software engineer or data scientist who specializes in using PyTorch, an open-source machine learning library, to build and deploy deep learning models. Their responsibilities typically include designing neural network architectures, training and evaluating models, and optimizing code for performance. PyTorch Developers work in fields such as artificial intelligence, computer vision, and natural language processing, collaborating with teams to solve complex problems using machine learning. They are proficient in Python and have a strong understanding of deep learning concepts. Additionally, they often contribute to research, development, and the deployment of AI solutions in production environments.

What are the key skills and qualifications needed to thrive as a PyTorch developer, and why are they important?

To thrive as a Pytorch Developer, you need strong programming skills in Python, a solid grasp of machine learning concepts, and experience with deep learning frameworks—especially PyTorch itself. Familiarity with tools like CUDA, Jupyter Notebooks, and version control systems (e.g., Git) is typically expected, along with knowledge of cloud platforms or relevant certifications. Problem-solving ability, effective collaboration, and clear communication are crucial soft skills for success in this role. These skills and qualities are vital for efficiently building, optimizing, and deploying machine learning models in real-world applications.

What is the difference between Pytorch Developer vs Machine Learning Engineer?

AspectPytorch DeveloperMachine Learning Engineer
Required CredentialsBachelor's or higher in CS, experience with PyTorchBachelor's or higher in CS, data science, or related field, with ML experience
Work EnvironmentResearch labs, AI startups, tech companies focusing on deep learningTech companies, finance, healthcare, often involving deployment and scaling ML models
Industry UsagePrimarily in AI research and development teamsAcross industries implementing ML solutions in production

While both roles require knowledge of machine learning and experience with PyTorch, a Pytorch Developer mainly focuses on developing and optimizing deep learning models using PyTorch. A Machine Learning Engineer often has a broader scope, including deploying, maintaining, and scaling ML models across various platforms and industries.

What are some common challenges PyTorch developers face when deploying machine learning models to production environments?

Pytorch Developers often encounter challenges when transitioning models from research to production, such as optimizing model performance for inference speed and memory usage, ensuring compatibility with deployment frameworks like TorchScript or ONNX, and managing dependencies across different systems. Additionally, integrating PyTorch models into existing software stacks and maintaining reproducibility can be complex. Collaborating closely with DevOps and data engineering teams is crucial to address these issues and ensure smooth deployment.
What are popular job titles related to Pytorch Developer jobs in Seattle, WA? For Pytorch Developer jobs in Seattle, WA, the most frequently searched job titles are:
What job categories do people searching Pytorch Developer jobs in Seattle, WA look for? The top searched job categories for Pytorch Developer jobs in Seattle, WA are:
What cities near Seattle, WA are hiring for Pytorch Developer jobs? Cities near Seattle, WA with the most Pytorch Developer job openings:
Pytorch Developer jobs near you
Infographic showing various Pytorch Developer job openings in Seattle, WA as of August 2026, with employment types broken down into 80% Full Time, and 20% Contract. Highlights an 60% In-person, and 40% Remote job distribution.

PyTorch Role/C++,Python

Staffingine LLC

Bellevue, WA • On-site

Full-time

Re-posted 26 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