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Manager 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 ... Build automated testing solutions in support of quality management objectives to reduce manual ...

... MLOps knowledge who can lead technical initiatives and deliver scalable AI solutions. Key ... Collaborate with Product Managers, Data Scientists, Software Engineers, and Business SMEs. * Mentor ...

Data Engineer

Columbus, OH

$110K - $132K/yr

Follow and promote software engineering, DataOps, and MLOps best practices. Minimum Requirements ... Understanding of data quality, data governance, and data lifecycle management principles.

Familiarity with Docker, Kubernetes, CI/CD , and MLOps practices. * Strong understanding of ... Excellent communication and stakeholder management skills. Preferred Skills * Banking or Financial ...

Familiarity with Docker, Kubernetes, CI/CD , and MLOps practices. * Strong understanding of ... Excellent communication and stakeholder management skills. Preferred Skills * Banking or Financial ...

Senior AI Engineer

Clifton Park, NY · On-site

$100K - $138K/yr

Establish MLOps best practices and technical KPIs tied to system uptime, model latency, and infrastructure efficiency * Mentor junior engineering staff and advise the Managing Director on technical ...

DevOps Engineer

Columbus, OH · On-site

$65 - $70/hr

Implement and manage GitOps workflows for continuous deployment and environment consistency * Build ... Experience with MLOps or AI/ML platforms (Kubeflow, model pipelines) * Knowledge of deployment ...

ERP AI Engineer - Manager

Columbus, OH · On-site

$99K - $232K/yr

As a Manager, you will lead teams of data scientists and ML engineers, manage client relationships ... with MLOps tooling and CI/CD pipelines for ML - Experience with vector databases and semantic ...

... MLOps capabilities (evaluation, monitoring, governance workflows, model/prompt/version management ... We are hiring an AI Engineer to build and operate the data, features, and GenAI foundations that ...

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How much do manager mlops engineer jobs pay per hour?

As of Aug 11, 2026, the average hourly pay for manager mlops engineer in the United States is $55.99, according to ZipRecruiter salary data. Most workers in this role earn between $40.14 and $74.52 per hour, depending on experience, location, and employer.
What cities are hiring for Manager Mlops Engineer jobs? Cities with the most Manager Mlops Engineer job openings:
What states have the most Manager Mlops Engineer jobs? States with the most job openings for Manager Mlops Engineer jobs include:
What are the most commonly searched types of Mlops Engineer jobs? The most popular types of Mlops Engineer jobs are:
A map of the United States highlighting the number of Manager Mlops Engineer job openings by state according to ZipRecruiter. The image is accompanied by a detailed chart listing the number of Manager Mlops Engineer job openings in each state, with California having the most at 2 and Alaska the least at 0.

MLOps Engineer (Databricks/AWS)

Inabia Solutions and Consulting, Inc.

Columbus, OH • On-site

Contractor

Posted 23 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.