Sr. ML Ops Engineer

Job Summary

This senior level position is responsible for building and operating the platforms, pipelines, and standards that support the development, deployment, and lifecycle management of machine learning models and data products. This role is expected to participate and lead communication with business customers as well as cross-functional IT staff, to support business teams delivering machine learning models and advanced analytics solutions.

Job Duties & Responsibilities

• Collaborate with cross-functional teams including Business Stakeholders, Business Analysts, Data Engineers, and other Software Engineers to identify and define requirements
• Design, develop, and support machine learning operations (MLOps) platforms and tools in support of data science activities
• Implement and maintain automated pipelines supporting the development, deployment, and operation of machine learning models and data products, ensuring scalability, reliability, and efficiency
• Develop and maintain documentation for platforms, pipelines, and operational processes
• Participate in code reviews, testing, and deployment activities, adhering to SDLC best practices
• Evaluate and recommend tools, patterns, and process improvements to enhance machine learning and advanced analytics delivery
• Collaborate with peers to share knowledge, support team capability development, and promote consistent engineering and MLOps practices

Job Specific Skills

• High proficiency in Python as a primary engineering language, with experience building, testing, and operating production systems supporting machine learning and analytics workloads
• High proficiency with SQL, and familiarity with Spark or other distributed data processing frameworks
• Experience establishing and operating a sustainable MLOps environment, including model deployment, pipeline automation, monitoring, and lifecycle management
• Strong software engineering fundamentals, including object-oriented design, unit testing, exception handling, and use of common design patterns
• Expertise in data modeling, data warehousing, and ETL/ELT processes supporting analytics and machine learning cases
• Hands-on experience with cloud-based data platforms and architectures, including Snowflake and Databricks
• Strong knowledge of CI/CD, DevOps, and release management practices used to deploy and operate production data and machine learning solutions
• Strong knowledge of SDLC processes, including Agile methodologies
• Excellent problem-solving skills and ability to troubleshoot complex issues in live production environments
• Strong communication and collaboration skills, with the ability to work effectively in a team environment

Education

Minimum: High school diploma or GED

Preferred: Bachelor’s degree - from accredited university - IT, MIS, Information Systems, Computer Science or related field

Experience

Minimum: 5 - 8 years related work experience