Bridge ML model development and core system operations
Design, build, and scale automated ML training, deployment, monitoring pipelines
Mature CI/CD and distributed infrastructure for AI products
Collaborate with data scientists, engineers, and product teams
Ensure reliability, performance, and observability of ML systems

🎯 Requirements

5+ years software/DevOps/data engineering; 2+ years in MLOps infra
Python proficiency with tests and Git
Kubernetes (EKS/GKE) and Docker; FastAPI
ML lifecycle tools: MLflow, Kubeflow, Spark/PySpark, Airflow
Cloud fundamentals (AWS, GCP) and security basics
Bachelor's or Master's in CS/DS/SE

🎁 Benefits

Competitive pay and benefits
Medical, dental, vision, and disability insurance (US)
401(k) matching (US) / RRSP with DPSP (Canada)
Flexible PTO plus 12 company days off
Learning & Development programs
Equipment and reimbursement for a productive remote environment

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