Senior MLOps Engineer

As a Senior MLOps engineer, together with Patterns 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 team’s 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.
  
  

• 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 solutions-oriented positive attitude.
• Strong demonstration of technical expertise in Computer Science, Machine Learning, Data Science, or a related field
• 4+ years of direct and extensive experience with AWS
• 3+ 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.