ML Engineer: Production ML & MLOps (Hybrid/Remote)

Central Insurance; Alpharetta (GA); Hybrid; USD 102,000 - 140,000; Full time

Job summary

Central Insurance is seeking a Machine Learning Engineer to partner with actuaries, data scientists, software engineers, and business stakeholders to design and deploy ML solutions.

You will build and maintain CI/CD pipelines for ML models, develop APIs and real-time scoring workflows, and ensure production readiness with monitoring and governance in a hybrid/remote-friendly environment.

Qualifications

• Master's or Bachelor's with ML production experience as stated.
• Experience deploying, maintaining, and supporting ML models in production environments.
• Experience developing or supporting APIs, microservices, batch scoring, or real-time inference.
• Experience with containerization, orchestration, or infrastructure automation tools (Docker, Kubernetes, Terraform).

Responsibilities

• Designs, builds, tests, deploys, and supports ML solutions aligned to business goals.
• Partners with diverse teams to transition models from experimentation to production.
• Develops and maintains automated deployment and CI/CD processes for ML models and pricing solutions.
• Develops and supports APIs, services, and batch/real-time scoring workflows for model inference.
• Supports pricing data pipeline development and validation for model scoring and monitoring.
• Implements model monitoring, observability, and logging for production health.

Skills

Python programming

CI/CD pipelines

APIs / microservices

Git / version control

SQL

Data pipelines

Model monitoring

Cloud / deployment automation

Education

Master's degree in Computer Science or Data Science

Bachelor's degree with 2 years ML production experience

4 years related ML production experience

Tools

Docker

Kubernetes

Terraform

Job description

Central Insurance is seeking a Machine Learning Engineer to partner with actuaries, data scientists, software engineers, and business stakeholders to design and deploy ML solutions.

You will build and maintain CI/CD pipelines for ML models, develop APIs and real-time scoring workflows, and ensure production readiness with monitoring and governance in a hybrid/remote-friendly environment.