Machine Learning Operations Engineer – MLOps

Role Overview

• Develop end-to-end backend pipelines for deploying machine learning models.
• Build Docker containers for trained machine learning models.
• Deploy Docker container images on Kubernetes engine.
• Maintain Kubernetes engine and virtual machines on Google Cloud Platform.
• Develop Flask and FastAPI frameworks in Python for deploying models as APIs.
• Deploy the models in production as REST APIs on cloud infrastructure.
• Observe and measure current product performance.
• Review the process and product performance data with the team to develop standard work.
• Document the process, code reviews and workflow to streamline product enhancements.
• Develop end-to-end pipeline for deploying software platform backend infrastructure.
• Build end-to-end methodology for backend modules of the cloud software platform.
• Choose the optimal technology stack for building out the elements of the software platform backend.
• Establish platform features and timelines for product roadmap.
• Integrate SQL database objects with the software platform.
• Integrate machine learning model REST API endpoints with software platform.
• Deploy the platform in production on cloud infrastructure.
• Work with a team of software engineers to enhance performance of the software platform and run continuous unit tests for deployed products.
• Observe and measure current product performance.
• Review the process and product performance data w/ team to develop standard work.
• Document the process, code reviews and workflow to streamline product enhancements.
• Maintain and monitor cloud infrastructure.
• Monitor the logs of customer usage of the products and test for any vulnerabilities.
• Maintain database systems and optimize for performance and costs.
• Provide unit and stress testing frameworks for cloud infrastructure services deployed in production environments.
• Document the process, code reviews and workflow to streamline product enhancements.

Requirements

• Must have a Bachelor’s degree in Computer Science or related field and 4 years of experience, including:
• Designing, implementing, debugging web technologies and server architectures (Java,JavaScript, NodeJS), databases in Cloud Infrastructure and with Python programming language
• Develop applications, API integrations on cloud infrastructures to handle customer data
• Utilizing and maintaining cloud infrastructure and services of Google Cloud Platform
• Employer will accept a Master’s degree and 2 years’ experience in lieu of the Bachelor’s plus 4.

Tech Stack

• Cloud
• Docker
• Flask
• Google Cloud Platform
• Java
• JavaScript
• Kubernetes
• Node.js
• Python
• SQL