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Mlops Engineer Jobs Near Me

MLOps Automation Senior Lead Engineer

Columbus, OH · On-site +1

$100K - $131K/yr

The MLOps Automation Engineering Senior Lead will lead a team responsible for building and deploying MLOps Automation for some of Huntington's most valuable and most challenging data-driven projects.

The ideal candidate is a hands-on engineer with strong Python expertise, cloud experience, and MLOps knowledge who can lead technical initiatives and deliver scalable AI solutions. Key ...

Data Engineer

Columbus, OH · On-site

$110K - $132K/yr

Follow and promote software engineering, DataOps, and MLOps best practices. Minimum Requirements * Must be authorized to work in the U.S. now and in the future. * Bachelor's degree in Computer ...

AI Engineer Location: Columbus, OH (Onsite) We are looking for an experienced AI Engineer to join ... Familiarity with Docker, Kubernetes, CI/CD , and MLOps practices. * Strong understanding of ...

AI Engineer Location: Columbus, OH (Onsite) We are looking for an experienced AI Engineer to join ... Familiarity with Docker, Kubernetes, CI/CD , and MLOps practices. * Strong understanding of ...

DevOps Engineer

Columbus, OH · On-site

$65 - $70/hr

... Engineer (GitOps / Kubernetes / AWS) Location: Columbus, OH (Onsite) Job Type: Contract-to-Hire ... Experience with MLOps or AI/ML platforms (Kubeflow, model pipelines) * Knowledge of deployment ...

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MLOps Engineer (Databricks/AWS)

Inabia Solutions and Consulting, Inc.

Columbus, OH • On-site

Contractor

Posted 29 days ago


Job description

Overview
Inabia is seeking an MLOps Engineer (Databricks/AWS) to design, develop, and maintain end-to-end machine learning operations pipelines on Databricks running on AWS. This role demands deep hands-on expertise with Databricks Machine Learning, MLflow, and a broad suite of AWS services to build scalable, production-grade ML systems. The ideal candidate will partner closely with Data Scientists, Data Engineers, and Platform Engineering teams to productionize models and ensure robust, governed, and cost-efficient deployments.
Locations: Columbus, OH - Dallas, TX - Atlanta, GA (Onsite only)
Responsibilities
  • Design, develop, and maintain end-to-end MLOps pipelines on Databricks running on AWS.
  • Build and automate machine learning workflows covering data preparation, feature engineering, model training, evaluation, deployment, and monitoring.
  • Deploy and manage ML models using MLflow Model Registry and Databricks Model Serving.
  • Develop and maintain CI/CD pipelines for ML solutions across development, staging, and production environments.
  • Collaborate with Data Scientists to productionize machine learning models and ensure reliable, repeatable deployments.
  • Monitor model health, prediction quality, data drift, and system performance, and implement automated retraining strategies where required.
  • Optimize Databricks workloads for performance, scalability, and cost efficiency.
  • Implement Infrastructure as Code using Terraform to provision and manage Databricks and AWS resources.
  • Ensure platform security, governance, and compliance using Unity Catalog and AWS IAM.
  • Troubleshoot production issues, perform root cause analysis, and continuously improve platform reliability.
  • Document MLOps processes, deployment standards, and operational best practices.

Key Qualifications
  • 10+ years of relevant experience in MLOps or a closely related data/ML engineering discipline.
  • Strong hands-on experience with Databricks Machine Learning.
  • Proficiency in Python, PySpark, and SQL for developing and operationalizing machine learning solutions.
  • Hands-on experience with MLflow for experiment tracking, model registry, model versioning, and lifecycle management.
  • Experience deploying and managing machine learning models using Databricks Model Serving and batch inference pipelines.
  • Strong understanding of the end-to-end ML lifecycle, including feature engineering, training, validation, deployment, monitoring, and retraining.
  • Experience building scalable ML pipelines using Databricks Workflows and Delta Lake.
  • Hands-on experience with AWS services including S3, IAM, EC2, Lambda, ECR, ECS/EKS, CloudWatch, and Secrets Manager.
  • Experience implementing CI/CD pipelines for Databricks and ML workloads using Git, Bitbucket, Jenkins, and Databricks Asset Bundles (DAB).
  • Experience with infrastructure automation using Terraform.
  • Strong understanding of Apache Spark architecture, optimization, and distributed data processing.
  • Experience working with Unity Catalog for governance, security, and access management.
  • Knowledge of model monitoring, data drift detection, and automated retraining strategies.
  • Understanding of MLOps best practices including reproducibility, versioning, testing, and governance.
  • Excellent analytical, problem-solving, and communication skills.

Preferred Qualifications
  • Experience with multi-environment Databricks deployments spanning development, staging, and production.
  • Familiarity with cost optimization strategies for large-scale Databricks and AWS workloads.
  • Prior experience documenting MLOps operational standards for cross-functional teams.