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PyTorch Internals Engineer (Task-Based, Remote)

afterquery experts New York City Metropolitan Area
Remote
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AI Summary

This is a task-based role for PyTorch experts focusing on low-level internals. Complete up to 3 short PyTorch tasks for $150 each, requiring deep custom autograd, CUDA/tensor extensions, or ATen-level experience. Fully remote with rolling onboarding starting next week, offering flexibility and a low time commitment.

Key Highlights
$150 per task with up to 3 tasks available
Fully remote work with flexible scheduling
Requires deep, internals-level PyTorch experience
Key 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
Technical Skills Required
PyTorch CUDA ATen
Benefits & Perks
$150 per task
Fully remote
Low time commitment
Nice to Have
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

Job Description


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.

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