Machine Learning Ops Engineer to build & support scalable, highly available and robust Machine Learning (ML) /Deep Learning (DL) platform using ML/DL frameworks, High-Performance Computing (HPC) machines, Data Science tools, products & services in cloud and on-premises for client’s data & analytics organization.
Role will expose you to cutting edge technologies related to ML/DL and the ideal candidate will be driven, focused and enthusiastic about learning new technologies and implement them.
Responsibilities
Build, install, configure, manage, and scale state-of-the-art machine learning platform in cloud (Azure preferred) & on-premises powering client’s Data & Analytics products and solutions.
Work with data scientists, architects, DevOps engineers, and vendors to implement scalable ML/DL solutions in cloud and on-premises to solve complex problems.
Creating & maintaining ML/DL pipelines and overall ML/DL workflow orchestration including but not limited to data collection, prep, transform, analyze, experiment, train, validate, serve, monitor, etc.
Implement ML/DL solutions addressing performance, scalability, and the governance/ traceability of machine learning models.
Iterate quickly through latest technologies, products, frameworks, and R&D on latest information related to ML/DL frameworks, tools & services.