ML Ops Lead/Architect Full Time

PRACYVA

Project Summary ML OPS & Data Processing Pipleline on AWS Platform

(Essential Skills) ML OPS, AWS ‘

–MLOps Platform architectural design.
–Understanding of Data pipelines, ML training/deployment: develop, maintain and deploy code via Python AWS APIs.
–DevOps for develop and deploy Python API programs via dockerization/package to AWS.
–Advanced level knowledge of DevOps with 8+ years of experience.
–Strong command of Python language.
–2 years experience working with AWS.
–2 years experience working with Terraform.
–Basic knowledge of ML (unsupervised/supervised learning).
–Expert in Data Engineering and building data pipelines, implementing Algorithms in a distributed environment.
–Strong understanding/expertise in building REST APIs/Micro services architecture.
–Advanced level knowledge of software development life cycleg17.