MLOps Engineer: Deploy, Observe & Scale AI

Speria; Atlanta (GA); On-site; USD 120,000 - 180,000; Full time

Job summary

Speria MTech, based in Atlanta, is seeking a highly skilled Machine Learning Operations (MLOps) Engineer. You will build and maintain infrastructure, deployment workflows, and platform capabilities to run Applied AI solutions reliably in production.

The role focuses on model deployment, scalable serving, orchestration, monitoring, and lifecycle management across Speria MTech’s platforms, working with ML and Data Engineers to ensure production-ready, observable systems.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, Information Systems, or a related field.
• 2–4 years of software, data engineering, MLOps, or platform engineering experience.
• Experience building and maintaining production systems with deployment pipelines.
• Experience deploying and operating data or ML systems in cloud environments.
• Strong Python programming with scripting and deployment automation.
• Experience with ML lifecycle tools (e.g., MLflow).
• Experience designing and managing CI/CD pipelines for ML systems.
• Experience with Databricks or similar platforms for ML lifecycle, tracking, governance, serving.
• Experience implementing monitoring, logging, observability for production systems.
• Strong understanding of performance, scalability, cost optimization.

Responsibilities

• Build and maintain deployment pipelines for ML and optimization services.
• Design scalable model serving patterns (APIs, batch jobs, workflows) for downstream systems.
• Manage model lifecycle: packaging, versioning, promotion, rollback, and deployment automation.
• Implement observability and alerting across model services and production workflows.
• Optimize model-serving systems for performance, scalability, and cost in cloud environments.
• Collaborate with ML Engineers to productionize models and workflows.
• Work with Data Engineers to ensure data inputs and pipelines are reliable.
• Standardize deployment practices to reduce complexity across AI systems.
• Support orchestration of workflows linking models to downstream applications.
• Maintain documentation for deployment architectures, workflows, and runbooks.

Skills

Python programming

CI/CD pipelines

MLOps

Collaboration with ML/Data teams

Education

Bachelor’s degree in Computer Science, Engineering, Information Systems

Tools

Docker

Databricks

MLflow

REST APIs

Job description

Speria MTech, based in Atlanta, is seeking a highly skilled Machine Learning Operations (MLOps) Engineer. You will build and maintain infrastructure, deployment workflows, and platform capabilities to run Applied AI solutions reliably in production.

The role focuses on model deployment, scalable serving, orchestration, monitoring, and lifecycle management across Speria MTech’s platforms, working with ML and Data Engineers to ensure production-ready, observable systems.