About this role
Introducing Moonlake, AI for creating world simulations.
SCOPE OF WORK
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
SCOPE OF WORK
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
About Embedding VC
Embedding VC is hiring for the member of technical staff - efficient ml role. NewJob aggregates active openings directly from Embedding VC's applicant tracking system, so this listing is current.
More jobs at Embedding VC →