ML Ops Engineer (Boston, MA)
Architect and operate end-to-end ML pipelines for training and deployment on GCP and AWS. Maintain system monitoring, alerting, and CI/CD automation for ML artifacts and infrastructure.
3 ML Ops Engineer jobs in United States available for remote work from home. Apply for positions such as ML Ops Engineer (Boston, MA), Senior ML Ops Engineer, ML Ops Infrastructure Engineer and more! Discover the best work-from-home or hybrid, full- and part-time jobs.
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Architect and operate end-to-end ML pipelines for training and deployment on GCP and AWS. Maintain system monitoring, alerting, and CI/CD automation for ML artifacts and infrastructure.
The Senior MLOps Engineer will own the end-to-end ML lifecycle, including model packaging, deployment, monitoring, and optimization for a custom inference platform powering a conversational shopping agent. Responsibilities include building and optimizing production-grade ML pipelines and defining strategies for model versioning, rollout, and lifecycle management.
You will design and maintain CI/CD pipelines and deployment infrastructure to transition ML models from research to production. Additionally, you will implement monitoring, A/B testing, and optimization strategies to ensure model performance and reliability at scale.
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