Staff Machine Learning Operations Engineer

Job Summary

We are seeking an experienced Machine Learning Operations (MLOps) Engineer to join and help shape our new MLOps team. This role focuses on deploying and optimizing machine learning models for always-on, high-availability systems in real-world, real-time unclassified and classified environments. As part of a new and growing team, you will have the unique opportunity to evangelize MLOps practices, contribute to the development of an on-premises development platform, and drive innovation in mission-critical applications.

Responsibilities

• Deploy and maintain high-performing ML models (e.g., ensembles of LSTMs and Random Forests) in real-time environments
• Monitor deployed models for drift or performance degradation and implement automated retraining pipelines.
• Implement advanced deployment strategies (e.g., Blue-Green, Canary, Champion-Challenger)
• Develop modular and flexible ML...

Join Canopy, a Ford-backed company, at the forefront of engineering advanced threat detection and deterrence products specifically designed for vehicles. Our mission is to eliminate vehicle crime and enhance mobility through cutting-edge consumer hardware, aftermarket connectivity, and AI-driven security solutions. As part of our team, you'll be at the forefront of innovation, helping to solve one of today’s most pressing challenges with cutting-edge solutions.

The Staff MLOps Engineer will lead the design, development, and implementation of scalable machine learning operations (MLOps) pipelines and infrastructure. This role is critical for ensuring that machine learning models are efficiently deployed, monitored, and maintained in production environments. The engineer will work closely with machine learning engineers, data scientists/engineers, and platform/SRE engineers to streamline and automate data ingestion, model deployment, ensuring high availability,...