Machine Learning Performance Engineer

We are looking for a ML Performance Engineer to work on deep learning performance optimization and benchmarking on modern GPU-based systems, with a strong focus on MLPerf Training and Inference workloads.
The primary models we work on include Llama 2, Llama 3, DeepSeek, and open-source GPT-style models (GPT-OSS).
This is a hands-on engineering role involving performance profiling, PyTorch optimization, large-scale distributed training, and building reproducible benchmarking environments, in close collaboration with other performance- and systems-focused engineers.
What You Will Do
Optimize training and inference pipelines for large language models such as Llama 2, Llama 3, DeepSeek, and GPT-OSS
Work on MLPerf Training and/or Inference benchmarks for LLM workloads
Profile GPU workloads to identify compute, memory, and communication bottlenecks
Improve scaling efficiency across multi-GPU and multi-node setups
Tune distributed training strategies (DDP, FSDP, ZeRO, ...