TorchBench diffusion ablations
Reproducible grid over schedulers and noise parameterizations; regression tests in CI for kernel upgrades.
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PyTorch Research Engineer (LLMs & vision)
Profile active · Apr 5
On the marketplace since Mar 15, 2026
I live in PyTorch: custom modules, distributed training, and turning paper ideas into reproducible training stacks—then handing off traced/quantized builds to platform teams.
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Reproducible grid over schedulers and noise parameterizations; regression tests in CI for kernel upgrades.
Internal cookbook: activation checkpointing, mixed precision, and gradient accumulation presets for 2–32 GPU jobs.
Staff ML Engineer
Polar Flux Labs · 2020 — Present
Staff ML engineer at Polar Flux Labs: PyTorch-centric research loops for multimodal models; Lightning + W&B sweeps with regression tests on CUDA upgrades. LoRA/QLoRA harness for 7B-class LLMs with eval gates, rollback-safe checkpoints, and human review queues. TorchBench-style ablations on diffusion schedulers; CI integration for kernel upgrades.
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