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.