Machine Learning Engineer

• Ensure that ML models can be effectively developed, deployed, managed, and monitored in production environments.
• Productionize ML models – integrate trained ML models with production systems.
• Build and manage ML pipelines – design, build, and maintain automated pipelines including data ingestion, data preprocessing, model training, validation, and deployment utilizing CI/CD practices.
• Infrastructure management – set up and manage infrastructure for ML workloads utilizing cloud platforms and containerization technologies.
• Monitoring and alerting – implement monitoring systems to track performance of ML models in production.
• Automation – automate various tasks within the ML workflow to improve efficiency and reproducibility.
• Performance optimization – identify ways to optimize the performance, efficiency, and scalability of ML models and their supporting infrastructure.
• Collaborate with teams and perform all other duties as assigned or directed.
• Work 100% onsite in Woodlawn, MD, 5 days a week.

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