Responsibilities
 Profile and enhance the performance of AI workloads across various hardware
platforms and machine learning frameworks
 Identify appropriate workloads and micro-benchmarks to be used for performance
analysis
 Follow industry trends in AI algorithms and models and evaluate them on the
company’s hardware
 Experiment with various model optimization techniques e.g. quantization, pruning,
compression, etc.
 Diagnose and troubleshoot complex heterogeneous computing systems and
software issues
 Collaborate with software and firmware teams to ensure that the system meets end
to end application performance goals while maintaining ease and efficiency of
software development
Requirements
 5+ years of experience with C++ and Python programming
 Hands on experience the internals of deep learning frameworks (e.g. PyTorch,
TensorFlow) and deep learning models
 General experience with the training and deployment of ML models
 Experience with distributed systems development, parallel programs or distributed
ML workloads
 Knowledge of best-practices in software development, including testing, profiling,
debugging, documentation, version control, issue tracking, and planning

 Deep understanding of CPU and GPU or custom ASICs (NPU, TPU, etc.)
architectures and low-level optimization techniques, memory hierarchy, instruction
scheduling, and performance trade-offs
 Experience with LLM development and/or deployment is a strong plus