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Internship Aws Machine Learning Jobs Near Me

Bespoke Labs

Machine Learning Engineer

Columbus, OH · On-site

... deep learning proficiency (PyTorch preferred; familiar with training loops, optimizers, mixed ... HPC (AWS, GCP, SLURM, or Ray) Solid understanding of evaluation methodology -- held-out sets ...

J.P. Morgan

WFP Machine Learning Scientist

Columbus, OH · On-site +1

Prior experience with public cloud technologies such as Amazon Web Services(AWS), Azure or Google ... machine learning. We have a strong partnership with Technology, which provides cutting edge data ...

The Hartford

Sr AI Machine Learning Engineer

Columbus, OH · Hybrid

$117K - $175K/yr

The Hartford is seeking Senior AI Machine Learning Engineer to build Machine Learning Operations ... Development experience developing solutions within AWS, GCP or both. * Experience developing ...

Whiz Global LLC

ML Engineer

Columbus, OH · On-site

Productionize machine learning models developed by Data Science teams. * Design and deploy Large Language Model (LLM) applications. * Integrate AI solutions into AWS and JPMorgan Chase internal cloud ...

The Hartford

Data Engineer

Columbus, OH

$110K - $132K/yr

The Hartford is developing industry-leading AI and machine learning capabilities to improve ... Familiarity with AWS and/or GCP cloud services. * Experience with source control systems such as ...

Huntington

Senior Data Scientist - AI

Columbus, OH · On-site +1

Strong experience with Cloud Machine Learning technologies (e.g., AWS Sagemaker) * Strong experience with machine learning environments (e.g., TensorFlow, scikit-learn, caret) * Strong understanding ...

Huntington

Senior Data Scientist - AI

Columbus, OH · On-site +1

Strong experience with Cloud Machine Learning technologies (e.g., AWS Sagemaker) * Strong experience with machine learning environments (e.g., TensorFlow, scikit-learn, caret) * Strong understanding ...

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How much do internship aws machine learning jobs pay per year?

As of Jul 29, 2026, the average yearly pay for internship aws machine learning in the United States is $42,584.00, according to ZipRecruiter salary data. Most workers in this role earn between $32,500.00 and $46,000.00 per year, depending on experience, location, and employer.
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Internship Aws Machine Learning jobs near you
A map of the United States highlighting the number of Internship Aws Machine Learning job openings by state according to ZipRecruiter. The image is accompanied by a detailed chart listing the number of Internship Aws Machine Learning job openings in each state, with California having the most at 2 and Hawaii the least at 0.
MLOps Engineer (Databricks/AWS)

MLOps Engineer (Databricks/AWS)

Inabia Solutions and Consulting, Inc.

Columbus, OH • On-site

Contractor

Posted 9 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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