Senior Research Engineer- Optimization
Luma AI
Palo Alto, CA, USA
Posted on Sunday, May 26, 2024
We are looking for engineers with significant problem solving experience in PyTorch, CUDA and distributed systems. You will work with Research Scientists to build & train cutting edge foundation models on thousands of GPUs.
Responsibilities
- Ensure efficient implementation of models & systems for data processing, training, inference and deployment
- Identify and implement optimization techniques for massively parallel and distributed systems
- Identify and remedy efficiency bottlenecks (memory, speed, utilization) by profiling and implementing high-performance CUDA, C++ and PyTorch code
- Work closely together with the research team to ensure systems are planned to be as efficient as possible from start to finish
- Build tools to visualize, evaluate and filter datasets
- Implement cutting-edge product prototypes based on multimodal generative AI
Experience
- Experience training large models using Python & Pytorch, including practical experience working with the entire development pipeline from data processing, preparation & data loading to training and inference.
- Experience with profiling CPU & GPU code in PyTorch, including Nvidia Nsight or similar.
- Experience writing & improving highly parallel & distributed PyTorch code, with familiarity in DDP, FSDP, Tensor Parallel, etc.
- Experience writing high-performance parallel C++. Bonus if done within an ML context with PyTorch, like for data loading, data processing, inference code.
- Experience with high-performance CUDA and writing custom PyTorch kernels. Top candidates will be able to utilize tensor cores; optimize performance with CUDA memory and other similar skills.
- Good to have experience working with Deep learning concepts such as Transformers & Multimodal Generative models such as Diffusion Models and GANs.
- Good to have experience building inference / demo prototype code (incl. Gradio, Docker etc.)
- Please note this role is not meant for recent grads.
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