Senior Machine Learning Engineer

Design, build, and deploy production-grade ML services, APIs, and applications that integrate predictive models into LMD platforms and scientific workflows

Package, containerize, and serve models for batch and real-time inference

Productionize research models by improving reliability, scalability, testing, and maintainability

Establish MLOps practices for experiment tracking, model/version management, validation, deployment, and rollback

Implement CI/CD pipelines and software engineering best practices to ensure code quality, maintainability, security, and reproducibility across ML applications

Monitor model performance, data quality, data/model drift, service health, usage and troubleshoot issues

Build and maintain reproducible workflows for data preparation, model training, inference, and evaluation in collaboration with ML scientists

Evaluate and implement emerging MLOps, model observability, and ML platform technologies that improve deployment speed, reliability, and scalability

• Communicate technical designs, trade-offs, metrics, and recommendations to technical and scientific partners