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 tasksFully remote, work on your own scheduleLow time commitment: ~2 hours active work per taskResponsibilitiesComplete up to 3 assigned technical tasks involving low-level PyTorch workEnsure code runs correctly through full runtime (including unattended/extended runtime)Complete tasks independently within a rolling onboarding scheduleRequired QualificationsFull-time professional or research experience with PyTorchDemonstrated 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 QualificationsBackground in ML, systems engineering, or distributed systems engineeringExperience with distributed training internalsExperience with compiler/graph-level work or numerical/algorithmic runtime optimizationContributions to PyTorch or adjacent open-source librariesCompany DescriptionAfterQuery 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.