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Mlflow Jobs Near Me

Senior Software Engineer

Columbus, OH

$118K - $156K/yr

DataDog, MLflow 3 * GenAI: Experience with LLM orchestration, search systems, and context engineering Highly Competitive Candidates Highly competitive candidates will have more than two of the ...

New

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

Build scalable AI solutions using modern frameworks and infrastructure including vLLM, LangChain, LangGraph, MLflow, Databricks, Snowflake, and cloud-native platforms. * Perform exploratory data ...

Build scalable AI solutions using modern frameworks and infrastructure including vLLM, LangChain, LangGraph, MLflow, Databricks, Snowflake, and cloud-native platforms. * Perform exploratory data ...

Familiarity with tools such as MLflow for model experimentation and registration, Git for version control, and agile frameworks using tools like Azure DevOps. Skills / Knowledge / Experience:

Sr. Data Engineer

Columbus, OH · On-site

$110 - $160/hr

Track experiments, manage models, and support deployment using MLflow * Define and execute model evaluation frameworks including both ML and AI agent performance * Designs and implements physical ...

New

Familiarity with tools such as MLflow for model experimentation and registration, Git for version control, and agile frameworks using tools like Azure DevOps. Skills / Knowledge / Experience:

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MLOps Engineer (Databricks/AWS)

Inabia Solutions and Consulting, Inc.

Columbus, OH • On-site

Contractor

Re-posted 15 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.