Machine Learning Jobs in Columbus, OH
Machine Learning jobs in Columbus are concentrated in the Short North tech corridor, the Easton area, and the growing Franklinton innovation district, with strong demand across fintech, healthcare AI, and enterprise software. Employers hiring right now include JPMorganChase, Path Robotics, and Mimecast. Scan the live roles below and apply to whichever ones fit.
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Showing 5 of 20+ Machine Learning jobs
Lead Machine Learning Engineer
Location: Fully Remote (U.S.)
Employment Type: Full-Time / Permanent
Our client is seeking a Lead Machine Learning Engineer to help build and scale the machine learning systems that power critical business decisions across Marketing, Finance, Product, and Customer Experience. This is an opportunity to join a collaborative engineering organization where you'll design, deploy, and operate production-grade machine learning platforms that enable data scientists to deliver high-impact models reliably and efficiently. This role is ideal for an experienced Machine Learning Engineer who enjoys building scalable ML infrastructure, improving developer productivity, and ensuring machine learning systems perform reliably in production.
Responsibilities
- Design, build, deploy, and maintain scalable machine learning systems and production ML pipelines.
- Partner closely with Data Scientists to productionize machine learning models, forecasting solutions, and simulation workflows.
- Develop reusable tools, services, and infrastructure that accelerate the path from experimentation to production.
- Build and improve ML deployment, monitoring, versioning, and operational workflows to increase reliability and scalability.
- Monitor production ML systems, investigate incidents, troubleshoot issues, and implement long-term improvements.
- Design solutions that provide reproducibility, lineage, governance, and visibility across complex ML workflows.
- Integrate ML systems with upstream data sources, feature stores, cloud data platforms, APIs, and downstream business applications.
- Develop dashboards, monitoring, and reporting capabilities that help stakeholders evaluate model performance and business impact.
- Collaborate with engineering, data science, and business teams to deliver reliable machine learning solutions.
- Mentor engineers, share best practices, and contribute to architecture and engineering standards.
Required Qualifications
- Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related quantitative field.
- 5+ years of experience designing, deploying, and supporting production machine learning systems.
- Strong Python programming and software engineering experience.
- Hands-on experience building and maintaining machine learning pipelines from development through deployment and production support.
- Experience with production monitoring, logging, alerting, debugging, and incident response for ML systems.
- Experience deploying ML models using modern MLOps practices and tools.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
- Experience with Infrastructure as Code tools such as Terraform.
- Strong understanding of CI/CD, APIs, containerization, and production software development best practices.
- Excellent communication skills with the ability to collaborate effectively across technical and non-technical teams.
Preferred Qualifications
- Master's or Ph.D. in Computer Science, Engineering, Statistics, Mathematics, or a related field.
- Experience with ML platforms and orchestration tools such as MLflow, Airflow, Kubeflow, Dagster, Databricks, Snowflake, Spark, or dbt.
- Experience building shared ML platforms, developer tooling, or reusable infrastructure for machine learning teams.
- Experience with customer lifetime value modeling, forecasting, recommendation systems, fraud detection, or risk modeling.
- Background working in insurance, financial services, or another highly regulated industry.
- Experience supporting large-scale, cloud-based production ML environments.
What We're Looking For
We're looking for an engineer who has owned machine learning systems throughout their lifecycle—not just developed models, but deployed, monitored, maintained, and continuously improved them in production. The ideal candidate enjoys solving complex engineering challenges, building scalable platforms, and partnering closely with data scientists and business stakeholders to deliver reliable machine learning solutions.
Compensation & Benefits
- Salary: $164,000 - $205,000
- Competitive bonus opportunity
- Equity offering
- Comprehensive benefits package
- Fully remote within the United States
Lead Machine Learning Engineer
Location: Fully Remote (U.S.)
Employment Type: Full-Time / Permanent
Our client is seeking a Lead Machine Learning Engineer to help build and scale the machine learning systems that power critical business decisions across Marketing, Finance, Product, and Customer Experience. This is an opportunity to join a collaborative engineering organization where you'll design, deploy, and operate production-grade machine learning platforms that enable data scientists to deliver high-impact models reliably and efficiently. This role is ideal for an experienced Machine Learning Engineer who enjoys building scalable ML infrastructure, improving developer productivity, and ensuring machine learning systems perform reliably in production.
Responsibilities
- Design, build, deploy, and maintain scalable machine learning systems and production ML pipelines.
- Partner closely with Data Scientists to productionize machine learning models, forecasting solutions, and simulation workflows.
- Develop reusable tools, services, and infrastructure that accelerate the path from experimentation to production.
- Build and improve ML deployment, monitoring, versioning, and operational workflows to increase reliability and scalability.
- Monitor production ML systems, investigate incidents, troubleshoot issues, and implement long-term improvements.
- Design solutions that provide reproducibility, lineage, governance, and visibility across complex ML workflows.
- Integrate ML systems with upstream data sources, feature stores, cloud data platforms, APIs, and downstream business applications.
- Develop dashboards, monitoring, and reporting capabilities that help stakeholders evaluate model performance and business impact.
- Collaborate with engineering, data science, and business teams to deliver reliable machine learning solutions.
- Mentor engineers, share best practices, and contribute to architecture and engineering standards.
Required Qualifications
- Bachelor's degree in Computer Science, Engineering, Mathematics, Statistics, or a related quantitative field.
- 5+ years of experience designing, deploying, and supporting production machine learning systems.
- Strong Python programming and software engineering experience.
- Hands-on experience building and maintaining machine learning pipelines from development through deployment and production support.
- Experience with production monitoring, logging, alerting, debugging, and incident response for ML systems.
- Experience deploying ML models using modern MLOps practices and tools.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud Platform.
- Experience with Infrastructure as Code tools such as Terraform.
- Strong understanding of CI/CD, APIs, containerization, and production software development best practices.
- Excellent communication skills with the ability to collaborate effectively across technical and non-technical teams.
Preferred Qualifications
- Master's or Ph.D. in Computer Science, Engineering, Statistics, Mathematics, or a related field.
- Experience with ML platforms and orchestration tools such as MLflow, Airflow, Kubeflow, Dagster, Databricks, Snowflake, Spark, or dbt.
- Experience building shared ML platforms, developer tooling, or reusable infrastructure for machine learning teams.
- Experience with customer lifetime value modeling, forecasting, recommendation systems, fraud detection, or risk modeling.
- Background working in insurance, financial services, or another highly regulated industry.
- Experience supporting large-scale, cloud-based production ML environments.
What We're Looking For
We're looking for an engineer who has owned machine learning systems throughout their lifecycle—not just developed models, but deployed, monitored, maintained, and continuously improved them in production. The ideal candidate enjoys solving complex engineering challenges, building scalable platforms, and partnering closely with data scientists and business stakeholders to deliver reliable machine learning solutions.
Compensation & Benefits
- Salary: $164,000 - $205,000
- Competitive bonus opportunity
- Equity offering
- Comprehensive benefits package
- Fully remote within the United States
See All 20 Machine Learning Jobs in Columbus
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Find Machine Learning JobsMachine Learning Job Market in Columbus
Who's Hiring
Top Industries Hiring
- Biotechnology & Pharmaceuticals
- Fintech
- Banking & Financial Services
- Investment & Asset Management
- Insurance
Machine Learning Jobs in Columbus: Frequently Asked Questions
How do I get a machine learning job in Columbus?
The strongest path into Columbus machine learning roles runs through the city's fintech, healthcare, and enterprise software sectors, which concentrate hiring in areas like the Short North, Easton, and near the Ohio State University Research District. Candidates who can show production-grade model deployment or MLOps experience stand out locally. Networking through Columbus's active tech meetup scene and targeting mid-size tech firms and insurance companies also gives a meaningful edge over applicants relying on applications alone.
Which companies hire machine learnings in Columbus?
Companies currently hiring machine learnings in Columbus include JPMorganChase, Path Robotics, and Mimecast, per current listings on Migrate Mate as of August 2026. Columbus's employer mix skews toward financial services firms, major healthcare systems, and homegrown SaaS companies, many of which run their own in-house ML teams rather than outsourcing to agencies.
Are there remote machine learning jobs in Columbus?
Yes, machine learning work is among the more remote-compatible technical roles since most of the work involves data, code, and cloud infrastructure rather than on-site equipment. About 62% of machine learning openings tied to Columbus are remote or hybrid as of August 2026. Model development and research roles tend to be most fully remote, while MLOps and data engineering positions tied to Columbus healthcare or financial institutions more often require at least some on-site presence.
How can I get a machine learning job in Columbus with little or no experience?
The most realistic entry path in Columbus is landing a data analyst or junior data engineer role at one of the city's many insurance companies, regional banks, or healthcare systems, then moving into ML work as you build production experience. Columbus employers at that level regularly hire candidates with a strong portfolio of personal or academic projects. Ohio State's proximity also means contract and research assistant roles occasionally open up that serve as a genuine foot in the door for early-career candidates.
Which industries hire the most machine learnings in Columbus?
The sectors hiring the most machine learnings in Columbus are Biotechnology & Pharmaceuticals, Fintech, and Banking & Financial Services, based on current listings on Migrate Mate as of August 2026. Columbus's outsized financial services presence, anchored by major insurance and banking headquarters, combined with a growing healthcare technology cluster and a mature retail analytics industry, collectively drive most of the city's sustained demand for machine learning talent.
See All 20 Machine Learning Jobs in Columbus
Find roles in Columbus that match your experience and apply in just a few clicks.
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