MLOps Engineer — Production ML Systems & Deployment

Speria; Dunwoody (GA); On-site; USD 120,000 - 170,000; Full time

Job summary

Speria MTech is seeking a skilled MLOps Engineer to operationalize machine learning and optimization systems. You will build deployment pipelines, serve models at scale, and manage lifecycle workflows across integrated platforms.

The role emphasizes observability, cost-efficient cloud deployments, and collaboration with ML Engineers and Data Engineers to productionize models and automate workflows. You will help standardize patterns and reduce operational complexity while enabling enterprise AI

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field.
• 2–4 years of software engineering, data engineering, MLOps, or platform engineering roles.
• Experience with cloud-based deployments and ML lifecycle tools (e.g., MLflow).
• Strong programming skills in Python and automation for deployment workflows.

Responsibilities

• Build and maintain deployment pipelines for ML and optimization services across dev, test, and prod.
• Design scalable model serving patterns via APIs, batch jobs, and scheduled workflows.
• Manage model lifecycle workflows: packaging, versioning, promotion, rollback, deployment automation.
• Implement and maintain observability, monitoring, and alerting across model services.
• Optimize model-serving systems for performance, scalability, and cost in cloud environments.
• Collaborate with ML Engineers to productionize models and intelligent workflows.
• Work with Data Engineers to ensure data inputs and feature outputs are available.
• Standardize deployment practices to reduce operational complexity across AI systems.
• Support orchestration of workflows connecting models to downstream apps.

Skills

Python

CI/CD pipelines

Cloud deployments

Monitoring/Observability

Performance optimization

Containerization

REST APIs

Automation

Education

Bachelor’s degree in CS/Engineering/IS or related field

Tools

MLflow

Databricks

Docker

CI/CD tools

Job description

Speria MTech is seeking a skilled MLOps Engineer to operationalize machine learning and optimization systems. You will build deployment pipelines, serve models at scale, and manage lifecycle workflows across integrated platforms.

The role emphasizes observability, cost-efficient cloud deployments, and collaboration with ML Engineers and Data Engineers to productionize models and automate workflows. You will help standardize patterns and reduce operational complexity while enabling enterprise AI