Cloud ML Ops Engineer: Deploy, Monitor & Scale AI Models

Buzz Solutions, inc.; United States; Remote; USD 140,000 - 190,000; Full time

Job summary

Buzz Solutions, inc. seeks a seasoned backend/ML platform engineer to design and scale cloud-based ML workflows. You will work on building, deploying and maintaining API services and data pipelines in Python across cloud environments.

Responsibilities include containerizing services for Kubernetes, monitoring production systems, and implementing CI/CD pipelines while optimizing performance and costs.

Qualifications

• Bachelor’s degree in CS or related field and 5 years of experience.
• Experience designing, implementing, debugging web technologies and server architectures.
• Coding, testing and developing using Python.
• Experience in SQL and NO SQL databases in Cloud Infrastructure.
• Experience in developing backend applications, API integrations, data pipelines on cloud infrastructures to handle customer data.
• Utilizing and maintaining cloud infrastructure and services on Google Cloud/AWS/Azure Cloud.

Responsibilities

• Build and maintain the infrastructure needed to support machine learning development and deployment.
• Develop REST API and gRPC applications using Python for deploying models as APIs.
• Build end-to-end pipelines for model inference, backend and data on the cloud software platform.
• Integrate SQL and NoSQL database systems with the software platform.
• Work with model registries and MLOPs frameworks to deploy machine learning models.
• Setup tools and metrics to monitor, analyze drift and maintain machine learning models in production.
• Develop and maintain CI-CD pipelines to deploy ML based backend artifacts.
• Monitor the logs of customer usage of the products and test for any vulnerabilities.
• Containerize ML based backend applications and deploy container images on Kubernetes engine.
• Maintain cloud infrastructure including Kubernetes engine and virtual machines on Google Cloud Platform.
• Design and deploy cloud infrastructure, database systems and optimize 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 development and enhancements.
• Establish AI based software platform features and timelines for product roadmap.
• Review the process and product performance data w/ team to develop standard work.
• Suggest optimal and current technological stack for building out the elements of the ML-based software platform backend.
• Work with a team of software engineers to enhance the performance of the software platform and run continuous unit tests for deployed products.

Skills

Python

Backend development

Web technologies

API integrations

Cloud infrastructure

SQL / NoSQL databases

Education

Bachelor’s degree in Computer Science or related field

Master’s degree accepted with 3 years of experience in lieu of bachelor's +4

Job description

Buzz Solutions, inc. seeks a seasoned backend/ML platform engineer to design and scale cloud-based ML workflows. You will work on building, deploying and maintaining API services and data pipelines in Python across cloud environments.

Responsibilities include containerizing services for Kubernetes, monitoring production systems, and implementing CI/CD pipelines while optimizing performance and costs.