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Software Engineer, Systems ML - Compilers / Backend

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Key skills for this role

PythonCC++

Analyze and design effective compiler passes and optimizations. Implement and/or enhance code generation targeting machine learning accelerators
Work with algorithm research teams to map ML graphs to hardware implementations, model data-flows, create cost-benefit analysis and estimate silicon power and performance
Work with hardware architects to co-design hardware features that maximize performance, power efficiency and programmability
Contribute to the development of machine-learning libraries, intermediate representations, export formats, and analysis tools
Analyze and improve the efficiency, scalability, and stability of our toolchains. Optimize and tune kernels and compiled code to achieve latency targets for ML inference
Conduct design and code reviews. Evaluate code performance, debug, diagnose and drive resolution of compiler and cross-disciplinary system issues
Interface with other compiler-focused teams to evaluate and incorporate their innovations and vice versa

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience
2+ years experience developing compilers, toolchains, runtime, or similar code optimization software
Experience in software design and programming experience in Python and/or C/C++ for development, debugging, testing and performance analysis
Experience in AI framework development or accelerating models on hardware architectures (GPU, TPU, custom AI ASICs)

Experience of developing in a mainstream machine-learning framework, e.g. PyTorch, MLIR, Tensorflow or Caffe
Experience with machine-code generation or compiler back-ends for on-device inference workloads

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