Machine Learning Engineer (PyTorch)

AfterQuery is sourcing ML, systems, and distributed systems engineers with deep, internals-level PyTorch experience — custom autograd, CUDA/tensor extensions, ATen-level work, and distributed training internals. This is a task-based role: complete up to 3 short PyTorch tasks, $150 per task, fully remote, ~2 hours active work per task, rolling onboarding starting next week.

Why Apply

• $150 per task — complete up to 3 tasks
• Fully remote, work on your own schedule
• Low time commitment: ~2 hours active work per task
  
  

Responsibilities

• Complete up to 3 assigned technical tasks involving low-level PyTorch work
• Ensure code runs correctly through full runtime (including unattended/extended runtime)
• Complete tasks independently within a rolling onboarding schedule
  
  

Required Qualifications

• Full-time professional or research experience with PyTorch
• Demonstrated experience with internals-level PyTorch work (custom autograd functions, tensor/CUDA extensions, or ATen-level work)
• Access to suitable hardware (GPU-enabled machine or cloud instance)
  
  

Preferred Qualifications

• Background in ML, systems engineering, or distributed systems engineering
• Experience with distributed training internals
• Experience with compiler/graph-level work or numerical/algorithmic runtime optimization
• Contributions to PyTorch or adjacent open-source libraries
  
  

Company Description

AfterQuery is a research lab investigating the boundaries of artificial intelligence through novel datasets and experimentation. We're backed by top investors, including Y Combinator and Box Group, and support all leading AI labs.