Machine Learning Engineer (PyTorch)

Role Overview

Task-based Machine Learning Engineer (PyTorch) role focused on internals-level PyTorch (e.g., custom autograd, CUDA/tensor extensions, ATen-level work, and distributed training internals).

Compensation & Commitment

• $150 per short PyTorch task
• Complete up to 3 tasks
• Fully remote
• ~2 hours active work per task
• Rolling onboarding starting next week

Responsibilities

• Complete up to 3 assigned technical tasks involving low-level PyTorch work
• Ensure code correctness across the full runtime, including unattended/extended runtime
• Work independently and complete tasks within the rolling onboarding schedule

Required Qualifications

• Full-time professional or research experience with PyTorch
• Demonstrated internals-level PyTorch experience, such as:
  • Custom autograd
  • Tensor/CUDA extensions
  • ATen-level work
• Access to suitable GPU-enabled hardware (local GPU 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