Machine Learning Operations Engineer

Buzz Solutions

. Build and maintain infrastructure supporting machine learning development and deployment .

Posted 10/7/2026full-timeRemote • United StatesMid-LevelSeniorWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in building and maintaining cloud infrastructure for machine learning, including developing REST APIs and integrating SQL and NoSQL databases. Proficient in deploying models using Python and managing CI/CD pipelines within Google Cloud or similar environments.

Highest-signal resume keywords

Python DevelopmentGoogle Cloud InfrastructureREST API DevelopmentCI/CD Pipeline ManagementSQL and NoSQL Database Integration

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Machine Learning DeploymentBackend Application DevelopmentData Pipeline DevelopmentContainerizationKubernetesMLOps FrameworksUnit TestingStress TestingCloud Infrastructure DesignAPI Integration

Soft Skills

CollaborationDocumentationProblem-Solving

Tools & Technologies

Google CloudAWSAzureKubernetes EngineSQLNoSQLGRPCCI/CD ToolsMonitoring ToolsModel Registries

Industry Keywords

Machine LearningCloud InfrastructureWeb TechnologiesServer ArchitecturesProduct Development

Tech Stack

Tools & technologies

AWSAzureCloudGRPCKubernetesNoSQLPythonSQL

About the role

Key responsibilities & impact

Build and maintain infrastructure supporting 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
Set up 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 customer product-usage logs and test for vulnerabilities
Containerize ML-based backend applications and deploy container images on Kubernetes Engine
Maintain Google Cloud infrastructure, including Kubernetes Engine and virtual machines
Design and deploy cloud infrastructure and database systems while optimizing performance and costs
Provide unit and stress testing frameworks for cloud infrastructure services in production
Document processes, code reviews, and workflows to streamline product development and enhancements
Establish AI-based software platform features and timelines for the product roadmap
Review process and product performance data with the team to develop standard work
Suggest optimal and current technology stacks for the ML-based software platform backend
Work with software engineers to enhance platform performance and run continuous unit tests for deployed products

Requirements

What you’ll need

The candidate must have a bachelor’s degree in computer science or related field and 5 years of experience
Experience designing, implementing, and debugging web technologies and server architectures
Experience coding, testing, and developing using Python
Experience with SQL and NoSQL databases in cloud infrastructure
Experience developing backend applications, API integrations, and data pipelines on cloud infrastructures to handle customer data
Experience utilizing and maintaining Google Cloud, AWS, or Azure cloud infrastructure and services
Employer will accept a master’s degree and 3 years’ experience in lieu of the Bachelor’s plus 4
Buzz Solutions does not provide sponsorship for work authorizations in the United States at this time