Senior MLOps Engineer
12 hours ago
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.
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