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Mlflow Jobs in Ohio (NOW HIRING)

ClifyX

Machine Learning Engineer

Dayton, OH · On-site

Required : • Strong hands on experience with Core ML & Stats (optimization, supervised unsupervised learning) • NLP (semantic search, embeddings, text modeling) • MLOps (MLflow, Kubeflow ...

Bespoke Labs

Data Engineer

Columbus, OH · On-site

$110K - $132K/yr

... MLflow, W&B, or similar) Comfortable with Docker and cloud infrastructure (AWS or GCP) Solid grasp of ML storage formats: Parquet, HDF5, JSON Lines

Bespoke Labs

Data Engineer

Bowling Green, OH · On-site

$107K - $129K/yr

... MLflow, W&B, or similar) Comfortable with Docker and cloud infrastructure (AWS or GCP) Solid grasp of ML storage formats: Parquet, HDF5, JSON Lines

Bespoke Labs

Data Engineer

Cleveland, OH · On-site

$110K - $133K/yr

... MLflow, W&B, or similar) Comfortable with Docker and cloud infrastructure (AWS or GCP) Solid grasp of ML storage formats: Parquet, HDF5, JSON Lines

Aimpoint Digital

$97K - $128K/yr

Experience with PySpark, MLflow, Databricks Workflows, Unity Catalog, Databricks SQL, or similar tooling is strongly preferred * Familiarity with enterprise AI patterns such as RAG, agents, model ...

Bespoke Labs

Data Engineer

Toledo, OH · On-site

$112K - $135K/yr

... MLflow, W&B, or similar) Comfortable with Docker and cloud infrastructure (AWS or GCP) Solid grasp of ML storage formats: Parquet, HDF5, JSON Lines

Kobie Marketing

AI Engineer

Columbus, OH

Amazon CloudWatch, LangSmith, Langfuse, MLflow, or OpenTelemetry * Experience designing evaluation frameworks (MLFlow, DeepEval, LLM-as-judge, multi-turn regression) * Fluency with Git, Docker, and ...

Whiz Global LLC

ML Engineer

Columbus, OH · On-site

Strong experience with MLOps tools including MLflow, Kubeflow, SageMaker, or Vertex AI . * Experience implementing CI/CD pipelines for machine learning applications. * Experience designing scalable ...

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Mlflow information

What is the difference between Mlflow vs Data Scientist?

AspectMlflowData Scientist
Required CredentialsKnowledge of machine learning tools, Python, and data managementDegree in Data Science, Statistics, or related field; programming skills
Work EnvironmentData science teams, machine learning projects, software developmentResearch, data analysis, model development, cross-functional teams
Employer & Industry UsageTech companies, AI startups, data-driven organizationsVarious industries including tech, finance, healthcare, and retail

While Mlflow is a platform for managing the machine learning lifecycle, a Data Scientist focuses on analyzing data and building models. Mlflow tools support Data Scientists in tracking experiments, but the roles differ in scope and responsibilities.

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For Mlflow jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Mlflow jobs in Ohio look for?

The top searched job categories for Mlflow jobs in Ohio are:

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Mlflow jobs near you
Infographic showing various Mlflow job openings in Ohio as of August 2026, with employment types broken down into 57% Full Time, 20% Temporary, and 23% Contract. Highlights an 80% In-person, and 20% Remote job distribution.

MLOps Engineer (Databricks/AWS)

Inabia Solutions and Consulting, Inc.

Columbus, OH • On-site

Contractor

Posted 26 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.

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