Senior MLOps Engineer

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.

Responsibilities

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.

Required Skills

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

Preferred Skills

Airflow

AWS SageMaker

Experience with cloud-based ML deployments

Experience in pricing, merchandising, retail, analytics, or optimization

Senior ML Ops Engineer (Remote)

Overview

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.

Responsibilities

• 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.

Required Skills

• 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

Preferred 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!”