Machine Learning Engineer (PyTorch)

Job DescriptionWe're sourcing ML, systems, and distributed systems engineers with deep, internals-level PyTorch experience (e.g. custom autograd, CUDA/tensor extensions, ATen-level work, distributed training internals) — full-time professional or research experience required. Complete up to 3 short PyTorch tasks (~2 hrs active work each, plus background runtime). Pay: $150/task. Fully remote, rolling onboarding next week.Why Apply$150 per task, up to 3 tasksFully remoteMost tasks require only ~2 hours of active hands-on workResponsibilitiesComplete up to 3 assigned technical tasks involving low-level PyTorch workEnsure code runs correctly through full runtime, including any extended, unattended runtimeComplete tasks independently within a rolling onboarding scheduleRequired QualificationsFull-time professional or research experience with PyTorchDemonstrated experience with internals-level PyTorch work — e.g. custom autograd functions, tensor/CUDA extensions, or ATen-level workAccess 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.