Senior Applied Research Engineer
The role optimizes large-scale distributed training and inference for foundation models, focusing on profiling, parallelization, memory efficiency, and productionization. It requires strong Python skills, multi-GPU training experience, and expertise in modern ML architectures.
About the job
Responsibilities
- Profile end-to-end distributed training runs to identify bottlenecks across compute, GPU memory, and inter-GPU communication.
- Contribute to architectural decisions that improve the efficiency and reliability of large-scale training jobs, including developing Triton/CUDA kernels when needed.
- Design and implement model scaling, parallelization, and memory optimization techniques for training workloads with very large context sizes.
- Collaborate closely with ML researchers to diagnose architectural inefficiencies, ensure new research ideas scale efficiently in practice, and spread internal knowledge about model efficiency and optimization.
- Drive the productionization and serving of models from the research side, including improving inference efficiency through techniques such as quantization.
Requirements
- Strong understanding of modern ML architectures and large-scale training pipelines.
- Experience running distributed training jobs on multi-GPU systems.
- Advanced profiling and debugging skills across CPU, GPU, memory usage, latency, and inter-GPU communication.
- Strong programming skills in Python.
- Experience with model scaling and parallelization strategies, including tensor and pipeline parallelism.
Nice to Have
- Familiarity with NCCL, MPI, and distributed communication primitives.
- Knowledge of PyTorch and Triton internals.
- Programming experience with C++ and CUDA.
Benefits
- Competitive compensation with salary and equity.
- Comprehensive health coverage for you and your dependents.
- Paid parental leave for all new parents, inclusive of adoptive and surrogate journeys.
- Relocation support for employees moving to join the team in one of the company's office locations.
- A mission-driven, low-ego culture that values diversity of thought, ownership, and bias toward action.
Skills
Python, CUDA, Triton, PyTorch, C++, Nccl, Mpi, Distributed Training, Tensor Parallelism, Pipeline Parallelism, Quantization, Gpu Profiling, Model Optimization
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