Job Description We are looking for a senior contributor to design, develop and optimize AI frameworks for Inference. In this role, you will work with cross-geo teams to enhance the inference stack to ensure competitive performance on deep learning inference models with a specific focus on the PyTorch framework. The roles and responsibilities that you would need to perform may include the following: Design and develop SW techniques for AI frameworks - both HW-agnostic and HW-aware Contribute to enhancing and extending the Inference and Training capabilities in our Software stack Profile deep learning inference workloads as needed and identify optimization opportunities Qualifications BTech, MS or PhD in CS or related fields with an overall experience of 10 to 15 years At least 2 or 3 years of experience working on Inference frameworks/tools for inference for deep learning models that have been deployed/used by customers Architecture/Design contributions to Inference systems Detailed understanding of machine learning systems optimization and deployment techniques such as quantization Experience with optimization techniques for deployment of Large Language Models (LLMs) Deep implementation knowledge of transformers and inference specific optimizations Programming skills in Advanced C++, Python and parallel programming skills Ability to debug complex issues in multi-layered SW systems Understanding of SW integration across open source frameworks and internal framework layers Strong understanding of computer architecture Effective communication skills and experience with working in a cross-geo setup Preferred Experience working on and contributing to Inference serving solutions Knowledge of compiler algorithms for heterogeneous systems Knowledge of open source compiler infrastructure like LLVM or gcc Understanding of low-level kernels Benefits We offer a total compensation package that ranks among the best in the industry. It consists of competitive pay, stock, bonuses, as well as benefit programs which include health, retirement, and vacation. Working Model This role will be eligible for our hybrid work model which allows employees to split their time between working on-site at their assigned Intel site and off-site. In certain circumstances the work model may change to accommodate business needs. J-18808-Ljbffr