Senior Deep Learning Compiler Engineer - HW-SW Codesign
$152,000 - $287,500 per year
Apply (opens in a new tab)Senior Deep Learning Compiler Engineer - HW-SW Codesign
Posted yesterday
SENIORITY
Lead
SALARY
$152,000 - $287,500 per year
About the role
- Crafting and implementing compiler optimization techniques for deep learning network graphs.
- Designing novel graph partitioning and tensor sharding techniques for distributed training and inference.
- Performance tuning and analysis.
- Code-generation for NVIDIA GPU backends using open-source compilers such as MLIR, LLVM and OpenAI Triton.
- Designing user facing features in JAX and related libraries and other general software engineering work.
- Working closely with GPU hardware engineering teams to design AI compiler software features for next-generation GPUs.
- What we need to see:
- Bachelors, Masters or Ph.D. in Computer Science, Computer Engineering, related field (or equivalent experience).4+ years of relevant work or research experience in performance analysis and compiler optimizations.
- Ability to work independently, define project goals and scope, and lead your own development effort adopting clean software engineering and testing practices.
- Excellent C/C++ programming and software design skills, including debugging, performance analysis, and test design.
- Strong foundation in architecture of CPU, GPUs or other high performance hardware accelerators. Knowledge of high-performance computing and distributed programming.
- CUDA or OpenCL programming experience is desired but not required.
- Experience with the following technologies is a huge plus: XLA, TVM, MLIR, LLVM, OpenAI Triton, deep learning models and algorithms, and deep learning framework design.
- Strong interpersonal skills are required along with the ability to work in a dynamic product-oriented team. A history of mentoring junior engineers and interns is a bonus.
- Ways to stand out from the crowd:
- Experience working deep learning frameworks such as JAX, PyTorch or TensorFlow.
- Extensive experience with CUDA or with GPUs in general.
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