PyTorch Internals Engineer (Task-Based, Remote)
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
Key Responsibilities
Technical Skills Required
Benefits & Perks
Nice to Have
Job Description
AfterQuery is sourcing ML, systems, and distributed systems engineers with deep, internals-level PyTorch experience β 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 β complete up to 3 tasks
- Fully remote, work on your own schedule
- Low time commitment: ~2 hours active work per task
- 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
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- 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)
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- 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
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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