PyTorch Jobs in Computer Vision
Browse CV roles that require PyTorch across all industries and experience levels.
3 open positions
Open Positions
Perception Engineer, Senior
9 Mothers
Machine Learning Technical Manager
Autodesk
Senior Scientist, Computer Vision & Robotics
Charles River Analytics
What is PyTorch?
PyTorch is the dominant deep learning framework in computer vision research and, increasingly, in production. Its eager execution model makes debugging straightforward, and the surrounding ecosystem — torchvision, Lightning, Hugging Face — covers most of what a vision team needs out of the box.
Where PyTorch is used
Effectively the default across every vertical. If a job description mentions deep learning at all, PyTorch is the assumed framework unless it explicitly says otherwise.
Roles that ask for PyTorch
- Computer Vision Engineer
- Deep Learning Engineer
- Machine Learning Engineer
- Research Scientist, Vision
- Applied Scientist
Related skills & tools
PyTorch jobs — common questions
Is PyTorch experience essential for computer vision jobs?
For nearly all deep learning roles, yes. It is the most frequently named framework in CV job descriptions, and teams generally expect you to be productive in it from day one rather than transferring from TensorFlow.
What does production PyTorch involve beyond training?
Export to TorchScript or ONNX, compilation with torch.compile, serving through TorchServe or Triton, and profiling and optimising inference. Knowing the path from research checkpoint to deployed endpoint is what distinguishes engineering roles from research ones.
How does it compare with TensorFlow today?
PyTorch leads in research and has largely closed the deployment gap. TensorFlow retains a strong position in mobile and embedded through TFLite and in some established enterprise stacks, so the choice is now more about existing infrastructure than capability.