Backend Engineer

October 31

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Mechanized AI

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Machine Learning • MLOps • Data Engineering • Data Pipeline • Data Cleaning

11 - 50

Description

• Company Description: Mechanized AI is at the forefront of AI innovation, leveraging cutting-edge technology to transform legacy systems into modern, efficient, and scalable solutions. • We work with enterprise clients to breathe life into their existing software, ensuring that they can meet the demands of today’s fast-paced, digital landscape. • Our team thrives on solving complex challenges and delivering innovative solutions. • As an organization, we are committed to fostering an environment that encourages creativity, collaboration, and continuous learning.

Requirements

• 4+ years of industry experience as a Cloud Data Engineer/Backend Engineer. • Deep experience in Python (4+ years), and flask (2+ years). • Deep Cloud experience & experience designing & building cloud architectures for data-centric products end-to-end. • Azure, GCP or AWS Experience with Infrastructure as Code: Pulumi, Terraform. At least 2 years. • Experience with: authentication best practices (auth0, cognito), SQL & NoSQL on the cloud, network config (NLBs), logging and data streaming. • Experience with creating multi-tenant and single-tenant platform tools. • Dealt with building products via ECS, Flask, Python. • Knowledge of DevOps best practices. • Experience in Machine Learning or Deep Learning Projects that have lived in production. • DevOps pipeline experience from scratch, using CodePipeline or equivalents. • Experience engaging and interacting deeply with front-end team members. • Great to have Skills & Experience: Experience with data products on the cloud that manage TBs of data & millions of pipeline deployments per day. • Pyspark (1+ year) Security Experience. • AWS Solution Architect Associate or higher, ideal. • AWS Data Certificates. • Some experience with front end, ideally React. • Experience with designing & implementing large dataset architectures; streaming, batch datasets, data lakes & meshes. • Experience creating data pipelines on the cloud: Glue, EMR, serverless EMR, step functions, kafka/kinesis, storage, and equivalents.