Job Purpose
ML Deployment Engineer will be a key role in the ML deployment process to ensure the machine learning models are running well in production to support the business analytics needs.
The Job
Deploys and operationalizes machine learning models.
Monitors the operational ML pipeline.
Integrates with CI/CD pipeline.
Works closely with data science team, data engineering team and platform operation team.
Documents SOP and best practices and troubleshoots when issue arises.
Takes accountability in considering business and regulatory compliance risks and takes appropriate steps to mitigate the risks.
Maintains awareness of industry trends on regulatory compliance, emerging threats and technologies in order to understand the risk and better safeguard the company.
Highlights any potential concerns /risks and proactively shares best risk management practices.
Our Requirements
Deep programming background with a degree in a highly analytical discipline, like Computer Science, Mathematics, etc.
Total of 2-4 years of experience in managing machine learning projects end-to-end, with the last 12 months focused on MLOps.
Monitoring Build & Production systems using automated monitoring and alarm tools.
Knowledge of machine learning frameworks: TensorFlow, PyTorch, etc.
High level of integrity takes accountability of work and good attitude over teamwork.
Takes initiative to improve current state of things and adaptable to embrace new changes.
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