Member of Technical Staff - Efficient ML
Quick Summary
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.
Introducing Moonlake, AI for creating world simulations.
Dataloaders, fusion, activation remat, gradient checkpointing.
FSDP/ZeRO/tensor+pipeline parallel; NCCL tuning.
Nsight profiling, Triton/CUDA kernels, fused ops.
Flash-attention–style speedups, sequence packing, KV-cache tricks.
Low-latency serving, continuous batching, speculative decoding.
Quantization (GPTQ/AWQ), distillation, pruning.
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
Location & Eligibility
Listing Details
- Posted
- January 15, 2026
- First seen
- May 6, 2026
- Last seen
- May 8, 2026
Posting Health
- Days active
- 0
- Repost count
- 0
- Trust Level
- 12%
- Scored at
- May 6, 2026
Signal breakdown
Please let embedding-vc know you found this job on Jobera.
4 other jobs at embedding-vc
View all →Explore open roles at embedding-vc.
Similar Member Of Technical Staff jobs
View all →Browse Similar Jobs
Stay ahead of the market
Get the latest job openings, salary trends, and hiring insights delivered to your inbox every week.
No spam. Unsubscribe at any time.