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Employee Relations Associates, Inc. seeks a Senior ML Ops Engineer to support machine learning initiatives within Pricing and Merchandising. The role collaborates with Data Scientists to productionize models, build pipelines, and deploy ML solutions using cloud platforms.
The ideal candidate has strong Python and SQL skills, experience with CI/CD, and a track record of delivering production-grade ML pipelines. Remote work options are available for this senior role.
We are looking for a Senior ML Ops Engineer to support machine learning initiatives within Pricing and Merchandising.
This person will work closely with Data Scientists to take machine learning models and move them into production. The ideal candidate has strong Python and SQL skills along with experience building production pipelines, CI/CD processes, and deploying ML models.
Move machine learning models from Data Science into production.
Build and maintain ML pipelines and production applications.
Develop and support CI/CD processes.
Use Airflow or similar tools for workflow orchestration.
Deploy models using GCP Vertex AI, AWS SageMaker, or similar platforms.
Work closely with Data Scientists and Software Engineers.
Write and optimize SQL queries and data processes.
Troubleshoot production issues and improve existing ML workflows.
Apply software engineering best practices to ML development and deployments.
Strong Python programming experience
Software engineering experience
Experience with CI/CD
Experience building or supporting production data/ML pipelines
Experience working with Data Science teams
Strong problem-solving and communication skills
Airflow
AWS SageMaker
Experience with cloud-based ML deployments
Experience in pricing, merchandising, retail, analytics, or optimization
We are looking for a Senior ML Ops Engineer to support machine learning initiatives within Pricing and Merchandising.
This person will work closely with Data Scientists to take machine learning models and move them into production. The ideal candidate has strong Python and SQL skills along with experience building production pipelines, CI/CD processes, and deploying ML models.
Move machine learning models from Data Science into production.
Build and maintain ML pipelines and production applications.
Develop and support CI/CD processes.
Use Airflow or similar tools for workflow orchestration.
Deploy models using GCP Vertex AI, AWS SageMaker, or similar platforms.
Work closely with Data Scientists and Software Engineers.
Write and optimize SQL queries and data processes.
Troubleshoot production issues and improve existing ML workflows.
Apply software engineering best practices to ML development and deployments.
Strong Python programming experience
Strong SQL skills
Software engineering experience
Experience with CI/CD
Experience building or supporting production data/ML pipelines
Experience working with Data Science teams
Strong problem-solving and communication skills
GCP / Vertex AI
Airflow
AWS SageMaker
Experience with cloud-based ML deployments
Experience in pricing, merchandising, retail, analytics, or optimization
“ TalentBridge employees are eligible for many benefit offerings such as medical, dental, vision, life insurance, short term disability, 401(k) and holiday pay!”