Senior MLOps Engineer

Senior MLOps Engineer

As a Senior MLOps engineer, together with Pattern's Data Science and Engineering teams, you will create and maintain impactful solutions for our brands across the world. From traditional machine learning to cutting-edge AI, you will work and lead throughout the model lifecycle.

Responsibilities:

• Teamwork: MLOps is a team sport, and we require a contributor who can elevate everyone

in the MLOps organization. While technical skills are required, your communication and

teamwork skills will deliver tangible value to our teams as well as elevate the teams

capacity.

• Collaboration: Directly work with data science, engineering, and machine learning teams

around the world, including evening IST.

• Pipeline Management: Architect, implement, and maintain scalable ML pipelines, with

seamless integration from data ingestion to production deployment.

• Model Monitoring: Lead the operationalization of machine learning models, ensuring

hundreds of models are continuously monitored, retrained, and optimized in real-time

environments

• Deployment: Deploy machine learning platform solutions in the cloud, securely and cost

effectively.

• Reporting: Effectively communicate actionable insights across teams using both automatic

(e.g., alerts) and non-automatic methods.

The type of game-changing candidate we are looking for:

• Hungry: The position is for those who want to become an MLOps thought leader, mastering

and incorporating the latest best practices into an ML platform?

• Transparent: Willingness to identify and admit errors and seek out opportunities to

continually improve both in their own work and across the team.

• Clear Communicator: MLOps is a central node in a complex system. Clear, actionable, and

concise communication, both written and verbal is a must.

• Solution-Oriented: We focus on consistently delivering the best solutions with a solutionsoriented positive attitude.
• Strong demonstration of technical expertise in Computer Science, Machine Learning, Data

Science, or a related field

• Multiple years of direct and extensive experience with AWS
• Multiple years of experience building and managing MLOps platform tools
• Excited to empower DS with tools, practices, and training that simplify MLOps enough for

Data Science to increasingly practice MLOps on their own and own products in production.