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Ml Infrastructure Engineer Jobs in Ohio (NOW HIRING)

Whiz Global LLC

ML Engineer

Columbus, OH · On-site

Job Title: ML Engineer (AI/LLM & Cloud) Location: Jersey City, NJ (Hybrid - 3 Days Onsite) OR ... Build production-ready machine learning systems and infrastructure. * Productionize machine ...

Bjak

$120 - $180/hr

About the Role As an ML Platform Engineer, you will build the infrastructure and systems that power A1's AI capabilities. You will design and operate the systems behind the AI stack, from model ...

EssilorLuxottica

Data & ML Engineer

Mason, OH · On-site

$107K - $129K/yr

... ML infrastructure, CI/CD, DevOps, and MLOps pipelines to support model training and deployment ... Managing platform performance, cost optimization, reliability, and availability Managing data ...

Essilor

Data & ML Engineer

Mason, OH

$107K - $129K/yr

... ML infrastructure, CI/CD, DevOps, and MLOps pipelines to support model training and deployment ... Managing platform performance, cost optimization, reliability, and availability Managing data ...

EssilorLuxottica Group

Data & ML Engineer

Mason, OH · On-site

$107K - $129K/yr

... ML infrastructure, CI/CD, DevOps, and MLOps pipelines to support model training and deployment ... Managing platform performance, cost optimization, reliability, and availability Managing data ...

GE Aerospace

Software Engineer AI/ML

Evendale, OH · On-site

$105K - $126K/yr

We're looking for an AI Engineer to help transform GE Aerospace operational data into production ... Ensure AI/ML models deploy reliably to AWS infrastructure with proper monitoring, logging, and ...

GE Aerospace

Software Engineer AI/ML

Evendale, OH · On-site

$109K - $132K/yr

We're looking for an AI Engineer to help transform GE Aerospace operational data into production ... Ensure AI/ML models deploy reliably to AWS infrastructure with proper monitoring, logging, and ...

Mimecast

Senior ML Ops Engineer

Columbus, OH · On-site

$100K - $138K/yr

Senior ML Ops Engineer Overview As a Senior ML Ops Engineer at Mimecast, you will be a technical ... This role sits at the intersection of infrastructure engineering and machine learning. You will own ...

Mimecast

Senior ML Ops Engineer

Columbus, OH · On-site

$100K - $138K/yr

Senior ML Ops Engineer Overview As a Senior ML Ops Engineer at Mimecast, you will be a technical ... This role sits at the intersection of infrastructure engineering and machine learning. You will own ...

Mimecast Limited

Senior ML Ops Engineer

Columbus, OH · On-site

$148 - $222/hr

Senior ML Ops Engineer**## **Overview**As a Senior ML Ops Engineer at Mimecast, you will be a ... This role sits at the intersection of infrastructure engineering and machine learning. You will own ...

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Showing results 1-20

All JobsMl Infrastructure Engineer JobsMl Infrastructure Engineer Jobs in Ohio

Ml Infrastructure Engineer information

See Ohio salary details

$44.2K

$120.8K

$173K

How much do ml infrastructure engineer jobs pay per year?

As of Aug 18, 2026, the average yearly pay for ml infrastructure engineer in Ohio is $120,801.00, according to ZipRecruiter salary data. Most workers in this role earn between $102,200.00 and $134,000.00 per year, depending on experience, location, and employer.

What is the difference between Ml Infrastructure Engineer vs Data Engineer?

AspectML Infrastructure EngineerData Engineer
Required CredentialsBachelor's/Master's in CS, experience with cloud platforms, scripting, and ML toolsBachelor's/Master's in CS, experience with databases, ETL, and data pipelines
Work EnvironmentFocus on deploying and maintaining ML systems, cloud infrastructure, and automationDesigning and building data pipelines, managing large datasets, and data storage
Employer & Industry UsageTech companies, AI startups, research labsFinance, healthcare, e-commerce, and data-driven industries

The ML Infrastructure Engineer specializes in building and maintaining the infrastructure that supports machine learning models, focusing on deployment, scalability, and automation. In contrast, Data Engineers primarily develop data pipelines and manage large datasets to enable data analysis and business intelligence. Both roles require strong technical skills and often overlap, but their core focus areas differ significantly.

What are popular job titles related to Ml Infrastructure Engineer jobs in Ohio?

For Ml Infrastructure Engineer jobs in Ohio, the most frequently searched job titles are:

What job categories do people searching Ml Infrastructure Engineer jobs in Ohio look for?

The top searched job categories for Ml Infrastructure Engineer jobs in Ohio are:

What cities in Ohio are hiring for Ml Infrastructure Engineer jobs?

Cities in Ohio with the most Ml Infrastructure Engineer job openings:

Ml Infrastructure Engineer jobs near you
Infographic showing various Ml Infrastructure Engineer job openings in Ohio as of August 2026, with employment types broken down into 95% Full Time, 2% Part Time, and 3% Contract. Highlights an 85% Physical, 6% Hybrid, and 9% Remote job distribution, with an average salary of $120,801 per year, or $58.1 per hour.

ML Engineer

Whiz Global LLC

Columbus, OH • On-site

Other

Posted 26 days ago

Job description

Job Title: ML Engineer (AI/LLM & Cloud)

Location: Jersey City, NJ (Hybrid – 3 Days Onsite) OR Columbus, OH (5 Days Onsite)
Duration: Contract-to-Hire

Job Summary

We are seeking a highly experienced ML Engineer to design, build, deploy, and integrate enterprise-scale AI/ML solutions within the JPMorgan Chase ecosystem. This role focuses on engineering production-ready machine learning applications, Large Language Model (LLM) solutions, and cloud-native ML platforms while partnering closely with Data Science teams and business stakeholders.

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 Responsibilities
  • Design, develop, deploy, and maintain scalable AI/ML applications.
  • Build production-ready machine learning systems and infrastructure.
  • 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 platforms.
  • Develop scalable model serving and inference pipelines.
  • Implement CI/CD pipelines for ML applications.
  • Build monitoring, observability, model drift detection, and automated retraining solutions.
  • Optimize AI applications for performance, scalability, reliability, and cost.
  • Collaborate with Product Managers, Data Scientists, Software Engineers, and Business SMEs.
  • Mentor junior engineers and provide technical leadership through architecture guidance and code reviews.
  • Research and implement modern AI/ML technologies and best practices.
Required Qualifications
  • Bachelor''s or Master''s degree in Computer Science, Engineering, Data Science, or a related field.
  • 10+ years of hands-on experience developing and deploying machine learning solutions in production.
  • Expert-level programming experience with Python.
  • Basic understanding of Java or Scala.
  • Strong experience with software engineering principles, data structures, algorithms, and distributed systems.
  • Extensive experience with AWS Cloud.
  • Experience deploying applications across public cloud and enterprise cloud platforms.
  • Hands-on experience with Docker and Kubernetes.
  • Strong experience with MLOps tools including MLflow, Kubeflow, SageMaker, or Vertex AI.
  • Experience implementing CI/CD pipelines for machine learning applications.
  • Experience designing scalable ML infrastructure and distributed data processing systems.
  • Proven ability to lead technical initiatives and mentor engineering teams.
Preferred Qualifications
  • Experience building and deploying Large Language Model (LLM) solutions.
  • Hands-on experience with Amazon Bedrock.
  • Experience with Generative AI applications.
  • Strong understanding of TensorFlow, PyTorch, or Scikit-learn.
  • Experience with Deep Learning, NLP, or Computer Vision.
  • Experience with distributed model training and high-throughput inference systems.
  • Knowledge of model optimization and AI performance tuning.

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