Oversee the end-to-end lifecycle of Machine Learning (ML) models, ensuring they are effectively developed, deployed, monitored, and maintained in production environments.
Design, build, and maintain automated ML pipelines for data ingestion, preprocessing, training, validation, and deployment using CI/CD best practices.
Develop and optimize ML models, particularly in Natural Language Processing (NLP) and text generation.
Implement monitoring and alerting systems to track model performance and reliability.
Automate workflows to enhance efficiency, reproducibility, and scalability.
Continuously improve model and infrastructure performance.
Bachelor's degree in Computer Science, Engineering, Mathematics, or a related field with 10+ years of experience; a Master's or Ph.D. may substitute for some experience.
Minimum 5 years of hands-on experience designing, implementing, and maintaining ML pipelines.
Eligibility to obtain and maintain a Public Trust clearance (required by contract).
Deep understanding of ML concepts, algorithms, and frameworks (TensorFlow, PyTorch, scikit-learn).