Software Engineer, MTIA SW Performance Autotuning

We are looking for an experienced engineer to lead performance autotuning on MTIA — Meta's custom training and inference accelerator. You will lead the MTIA Software Performance Autotuning team (part of Infra Foundations) and own how we extract maximum performance from our hardware, automatically and at scale. Every kernel, every compiled graph, and every runtime configuration has a large space of possible implementations — tile sizes, scheduling, memory layouts, fusion decisions, precision choices — and the right one depends on the chip, the model, and the shape. Hand-tuning does not scale. The team's core mission is to make MTIA fast by default: building the search infrastructure, cost models, and tuning methodology that finds the best configuration without a human in the loop. As a technical leader, you will define our autotuning strategy, architect the search and benchmarking infrastructure, and partner closely with compiler, kernel, runtime, and product (e.g., Ads Ranking, Recommendation Systems, GenAI) teams to turn performance headroom into shipped speedups.

Autotuning operates across the full MTIA software stack — FX graphs, compiler, kernels, runtime, PyTorch — which means lots of cross-team collaboration. We partner closely with machine learning engineers across Ads, Instagram/Facebook, and Meta Superintelligence Labs teams whose models run on MTIA.