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Senior Machine Learning Operations (MLOps) Engineer

  • Senior Machine Learning Operations (MLOps) Engineer job type Posted on: Oct 22, 2026
  • Senior Machine Learning Operations (MLOps) Engineer experience level Eliassen Group
  • Senior Machine Learning Operations (MLOps) Engineer employment type Cincinnati, Ohio
  • Senior Machine Learning Operations (MLOps) Engineer salary Salary: $75 per hour
  • Senior Machine Learning Operations (MLOps) Engineer employment type Onsite
  • Senior Machine Learning Operations (MLOps) Engineer salary Full-time
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Job Title :

Senior Machine Learning Operations (MLOps) Engineer

Job Type :

Full-Time

Job Location :

Cincinnati Ohio United States

Remote :

No

Jobcon Logo Job Description :

View Full Description

Job Description

Job Description
Description:

On-site in Cincinnati, OH

 

Our client seeks a Senior Machine Learning Operations (MLOps) Engineer to design, build, and optimize scalable platforms and production ML systems across the end-to-end lifecycle. You will enable feature engineering, model development, automated deployment, monitoring, governance, and continuous improvement in cloud environments while partnering with data scientists, data engineers, software engineers, and business stakeholders. Experience in regulated industries is desirable.

 

Due to client requirements, applicants must be willing and able to work on a w2 basis. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance.

 

Rate: $75.00 to $85.00/hr. w2

Responsibilities:
  • Design, develop, deploy, and manage production-grade machine learning solutions.
  • Build scalable and reusable ML platforms for development, training, validation, deployment, and monitoring.
  • Implement best practices for model versioning, experimentation tracking, governance, and reproducibility.
  • Develop frameworks for batch and real-time inference.
  • Optimize ML systems for performance, reliability, maintainability, and cost.
  • Design and maintain automated CI/CD/CT pipelines for ML workflows.
  • Automate model testing, validation, deployment, rollback, and retraining.
  • Establish infrastructure-as-code and automated environment provisioning.
  • Build operational tooling for model lifecycle management across environments.
  • Design and support enterprise feature stores to improve reuse and governance.
  • Integrate ML solutions with data warehouses, data lakes, and operational sources.
  • Develop scalable data pipelines for training and inference.
  • Optimize data availability, quality, lineage, and observability.
  • Implement monitoring for model performance, data quality, and drift.
  • Establish alerting, observability, and incident management processes.
  • Develop strategies for retraining and continuous improvement.
  • Build and support low-latency scoring and prediction platforms.
  • Develop event-driven ML architectures using streaming technologies.
  • Implement MLOps governance standards and controls with security and compliance alignment.
  • Support auditability, explainability, lineage tracking, and documentation.
  • Collaborate with cross-functional teams and mentor junior engineers.
  • Drive adoption of modern ML engineering methodologies.
Experience Requirements:
  • 5+ years in Machine Learning Engineering, MLOps, Data Engineering, or Software Engineering.
  • 3+ years building and supporting production ML systems.
  • End-to-end ML lifecycle management experience.
  • Cloud experience with AWS, Azure, or GCP.
  • Experience with batch and real-time ML solutions and large-scale data.
  • ML and MLOps: lifecycle management, deployment and orchestration, experiment tracking and versioning, monitoring and observability, feature store and model registry, automated retraining, responsible AI and governance.
  • Cloud platforms: AWS SageMaker, Azure ML, or Google Vertex AI.
  • Programming: Python and SQL required; Java, Scala, or R preferred.
  • Data platforms: Snowflake, Databricks, IBM DB2 or equivalent, data lakes and cloud storage.
  • Data transformation: dbt, Spark, Pandas, PySpark.
  • DevOps and infrastructure: Git-based workflows, CI/CD tools, Terraform or IaC, Linux, shell scripting.
  • Containers and orchestration: Docker, Kubernetes, OpenShift preferred.
  • Streaming and real-time: Apache Kafka, event-driven architectures, real-time inference pipelines.
  • Monitoring and observability: Prometheus, Grafana, ELK, cloud-native solutions.
  • Preferred: enterprise feature stores, model registry and governance frameworks, real-time decisioning platforms, credit risk or fraud or customer analytics or recommender systems, MLFlow or Kubeflow or Airflow or Argo or Feast or SageMaker Pipelines, distributed systems, AI/ML regulatory frameworks, relevant cloud certifications.
Recruitment Transparency Notice
 
Eliassen Group values transparency in our recruitment practices. Please be advised that Eliassen Group utilizes artificial intelligence (AI) tools as part of its initial application screening and hiring process. You may receive email and SMS notifications from the Eliassen Virtual Recruiting Team (, 781-808-2924) inviting you to complete a brief voice screening as part of your application process. These tools assist our hiring teams in different ways, including but not limited to, assistance in reviewing application materials to help identify candidates whose qualifications most closely match the requirements of the position. All AI-assisted evaluations and responses are reviewed by human recruiters before any hiring decisions are made. The use of AI in our process is intended to support fairness, efficiency, and consistency, and Eliassen Group takes measures to prevent bias or discrimination in connection with its hiring practices. By proceeding, you acknowledge, agree, and consent to Eliassen Group’s use of these tools, including AI tools, as part of the application and hiring process.
 

Skills, experience, and other compensable factors will be considered when determining pay rate. The pay range provided in this posting reflects a W2 hourly rate; other employment options may be available that may result in pay outside of the provided range.W2 employees of Eliassen Group who are regularly scheduled to work 30 or more hours per week are eligible for the following benefits: medical (choice of 3 plans), dental, vision, pre-tax accounts, other voluntary benefits including life and disability insurance, 401(k) with match, and sick time if required by law in the worked-in state/locality.If anyone reaches out to you about an open position connected with Eliassen Group, please ensure that you are working directly with us by confirming the following:

· When you work with Eliassen Group, all email communication will come from an address, never Gmail, Yahoo, etc.

· Eliassen Group will never ask you for personal information (home address, bank account, or check routing number) until you have worked with someone clearly associated with Eliassen Group.

If you have any indication of fraudulent activity, please contact 

 
About Eliassen Group:
 
Eliassen Group is a strategic consulting firm that helps organizations reach further and achieve more through our technology, business advisory, and life sciences solutions. For nearly 40 years, we have combined exceptional people, deep domain expertise, and intelligent capabilities to expand our clients’ capacity and accelerate meaningful outcomes. We are driven by a purpose to positively impact the lives of our employees, clients, consultants, and the communities we serve.
 
Eliassen is committed to building a diverse and inclusive team from a variety of backgrounds, perspectives, and skills. We are an Equal Opportunity and Affirmative Action Employer and all employment decisions are based on merit, performance, and business needs. Eliassen does not discriminate on the basis of race, color, gender identity or expression, sexual preference or orientation, sex (including pregnancy, childbirth, and related medical conditions), marital status, creed, religion, physical or mental disability, genetic information, military or veteran status, age, ancestry, national origin, citizenship status, prohibited criminal record inquiries of applicants and employees, or any other category protected by federal, state, or local laws.
 
Don’t miss out on our referral program! If we hire a candidate that you refer us to then you can be eligible for a $1,000 referral check!
 

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Jobcon Logo Position Details

Posted:

Oct 22, 2026

Reference Number:

5cc92a15

Employment:

Full-time

Salary:

$75 per hour

City:

Cincinnati

Job Origin:

ziprecruiter

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Job Description

Job Description
Description:

On-site in Cincinnati, OH

 

Our client seeks a Senior Machine Learning Operations (MLOps) Engineer to design, build, and optimize scalable platforms and production ML systems across the end-to-end lifecycle. You will enable feature engineering, model development, automated deployment, monitoring, governance, and continuous improvement in cloud environments while partnering with data scientists, data engineers, software engineers, and business stakeholders. Experience in regulated industries is desirable.

 

Due to client requirements, applicants must be willing and able to work on a w2 basis. For our w2 consultants, we offer a great benefits package that includes Medical, Dental, and Vision benefits, 401k with company matching, and life insurance.

 

Rate: $75.00 to $85.00/hr. w2

Responsibilities:
  • Design, develop, deploy, and manage production-grade machine learning solutions.
  • Build scalable and reusable ML platforms for development, training, validation, deployment, and monitoring.
  • Implement best practices for model versioning, experimentation tracking, governance, and reproducibility.
  • Develop frameworks for batch and real-time inference.
  • Optimize ML systems for performance, reliability, maintainability, and cost.
  • Design and maintain automated CI/CD/CT pipelines for ML workflows.
  • Automate model testing, validation, deployment, rollback, and retraining.
  • Establish infrastructure-as-code and automated environment provisioning.
  • Build operational tooling for model lifecycle management across environments.
  • Design and support enterprise feature stores to improve reuse and governance.
  • Integrate ML solutions with data warehouses, data lakes, and operational sources.
  • Develop scalable data pipelines for training and inference.
  • Optimize data availability, quality, lineage, and observability.
  • Implement monitoring for model performance, data quality, and drift.
  • Establish alerting, observability, and incident management processes.
  • Develop strategies for retraining and continuous improvement.
  • Build and support low-latency scoring and prediction platforms.
  • Develop event-driven ML architectures using streaming technologies.
  • Implement MLOps governance standards and controls with security and compliance alignment.
  • Support auditability, explainability, lineage tracking, and documentation.
  • Collaborate with cross-functional teams and mentor junior engineers.
  • Drive adoption of modern ML engineering methodologies.
Experience Requirements:
  • 5+ years in Machine Learning Engineering, MLOps, Data Engineering, or Software Engineering.
  • 3+ years building and supporting production ML systems.
  • End-to-end ML lifecycle management experience.
  • Cloud experience with AWS, Azure, or GCP.
  • Experience with batch and real-time ML solutions and large-scale data.
  • ML and MLOps: lifecycle management, deployment and orchestration, experiment tracking and versioning, monitoring and observability, feature store and model registry, automated retraining, responsible AI and governance.
  • Cloud platforms: AWS SageMaker, Azure ML, or Google Vertex AI.
  • Programming: Python and SQL required; Java, Scala, or R preferred.
  • Data platforms: Snowflake, Databricks, IBM DB2 or equivalent, data lakes and cloud storage.
  • Data transformation: dbt, Spark, Pandas, PySpark.
  • DevOps and infrastructure: Git-based workflows, CI/CD tools, Terraform or IaC, Linux, shell scripting.
  • Containers and orchestration: Docker, Kubernetes, OpenShift preferred.
  • Streaming and real-time: Apache Kafka, event-driven architectures, real-time inference pipelines.
  • Monitoring and observability: Prometheus, Grafana, ELK, cloud-native solutions.
  • Preferred: enterprise feature stores, model registry and governance frameworks, real-time decisioning platforms, credit risk or fraud or customer analytics or recommender systems, MLFlow or Kubeflow or Airflow or Argo or Feast or SageMaker Pipelines, distributed systems, AI/ML regulatory frameworks, relevant cloud certifications.
Recruitment Transparency Notice
 
Eliassen Group values transparency in our recruitment practices. Please be advised that Eliassen Group utilizes artificial intelligence (AI) tools as part of its initial application screening and hiring process. You may receive email and SMS notifications from the Eliassen Virtual Recruiting Team (, 781-808-2924) inviting you to complete a brief voice screening as part of your application process. These tools assist our hiring teams in different ways, including but not limited to, assistance in reviewing application materials to help identify candidates whose qualifications most closely match the requirements of the position. All AI-assisted evaluations and responses are reviewed by human recruiters before any hiring decisions are made. The use of AI in our process is intended to support fairness, efficiency, and consistency, and Eliassen Group takes measures to prevent bias or discrimination in connection with its hiring practices. By proceeding, you acknowledge, agree, and consent to Eliassen Group’s use of these tools, including AI tools, as part of the application and hiring process.
 

Skills, experience, and other compensable factors will be considered when determining pay rate. The pay range provided in this posting reflects a W2 hourly rate; other employment options may be available that may result in pay outside of the provided range.W2 employees of Eliassen Group who are regularly scheduled to work 30 or more hours per week are eligible for the following benefits: medical (choice of 3 plans), dental, vision, pre-tax accounts, other voluntary benefits including life and disability insurance, 401(k) with match, and sick time if required by law in the worked-in state/locality.If anyone reaches out to you about an open position connected with Eliassen Group, please ensure that you are working directly with us by confirming the following:

· When you work with Eliassen Group, all email communication will come from an address, never Gmail, Yahoo, etc.

· Eliassen Group will never ask you for personal information (home address, bank account, or check routing number) until you have worked with someone clearly associated with Eliassen Group.

If you have any indication of fraudulent activity, please contact 

 
About Eliassen Group:
 
Eliassen Group is a strategic consulting firm that helps organizations reach further and achieve more through our technology, business advisory, and life sciences solutions. For nearly 40 years, we have combined exceptional people, deep domain expertise, and intelligent capabilities to expand our clients’ capacity and accelerate meaningful outcomes. We are driven by a purpose to positively impact the lives of our employees, clients, consultants, and the communities we serve.
 
Eliassen is committed to building a diverse and inclusive team from a variety of backgrounds, perspectives, and skills. We are an Equal Opportunity and Affirmative Action Employer and all employment decisions are based on merit, performance, and business needs. Eliassen does not discriminate on the basis of race, color, gender identity or expression, sexual preference or orientation, sex (including pregnancy, childbirth, and related medical conditions), marital status, creed, religion, physical or mental disability, genetic information, military or veteran status, age, ancestry, national origin, citizenship status, prohibited criminal record inquiries of applicants and employees, or any other category protected by federal, state, or local laws.
 
Don’t miss out on our referral program! If we hire a candidate that you refer us to then you can be eligible for a $1,000 referral check!
 

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