Member of Technical Staff - Efficient ML

Introducing Moonlake, AI for creating world simulations.

Training efficiency

• Dataloaders, fusion, activation remat, gradient checkpointing.

• FSDP/ZeRO/tensor+pipeline parallel; NCCL tuning.

GPU + kernel performance

• Nsight profiling, Triton/CUDA kernels, fused ops.

• Flash-attention–style speedups, sequence packing, KV-cache tricks.

Inference optimization

• Low-latency serving, continuous batching, speculative decoding.

• Quantization (GPTQ/AWQ), distillation, pruning.

Infra + reliability

• SLURM/K8s multi-node jobs, checkpoint hygiene.

• Determinism, env pinning, GPU failure handling.

We are committed to being an on-site, in-person team currently based in San Mateo