Developing and utilizing AI frameworks such as PyTorch and TensorFlow in enterprise level applications.
Working with IBM’s research team to develop next generation solutions for IBMs Telum series of on-chip hardware accelerators and the Spyre AI accelerator.
Collaborate closely with teams developing other components of the AI solution in ensuring robustness, high-quality code generation and suitability for developing programs exploiting compiled models as shared libraries used in deep learning and safety-critical execution environments on IBM Z platform for Linux on Z, LinuxOne, IBM Z Container Extension Platform and IBM Z/OS operating systems.
Provide engineering support for the AI on Z solution and deliver targeted changes for production customer releases.
Establish strong customer/partner relationships and trust through excellent execution and high-quality software development.
Work with the open-source community to drive and deliver code contributions to lead IBM efforts in AI development.
Required Technical and Professional Expertise
BS in Computer Science, Computer Engineering, Data Science/Data Analytics, or related field (or equivalent experience) plus 5+ years of professional experience in developing AI frameworks (TensorFlow, PyTorch, etc.) with enterprise-level applications.
Must have strong C, C++, and Python programming skills.
Familiarity working with and ability to develop user targeted Large Language Models (LLMs).
Experience working with industry standard C++ compilers and development frameworks.
Experience with machine-code generation or compiler back-end users.
Strong software engineering development discipline. Proficiency in data structures, algorithms, and the software development cycle.
Strong interpersonal, verbal and written communications skills.
Capability to achieve objectives under tight deadlines.
Experience executing tasks while managing competing priorities.
Experience working on and contributing to an active toolchain codebase.
Experience with CI/CD, Jenkins, Linux a plus.
Preferred Technical and Professional Expertise
MS/PhD degree in Computer Science, Computer Engineering, Data Science/Data Analytics, or related field.
Knowledge of compiler front-end technology.
Experience working with accelerator frameworks e.g. CUDA (Compute Unified Device Architecture) library for Nvidia.