This role focuses on optimizing large-scale financial modeling applications by implementing MLOps practices and maintaining end-to-end pipelines on AWS.
Description: We are seeking an experienced and highly skilled AWS Full Stack ML Engineer to operationalize and optimize our large-scale financial modeling applications. This role requires a unique blend of expertise in machine learning, software engineering, and AWS cloud infrastructure, with a strong focus on implementing robust MLOps practices to ensure scalability, reliability, and cost-efficiency. The ideal candidate will bridge the gap between data science and production systems, transforming data science prototypes into secure, high-performance, and compliant solutions in a fast-paced financial environment. Key Responsibilities Implement MLOps and CI/CD: Design, build, and maintain end-to-end MLOps pipelines for the continuous integration, training, deployment, and monitoring of ML models on AWS. System Design and Integration: Reengineer large scale model development code (from data scientists) and model application code (from software engineers) and seamlessly integrate into unified, production-ready systems. Education: A Bachelor's or Master's degree in Computer Science, Engineering, Statistics, or a related quantitative field Certifications (Preferred): AWS Certified Machine Learning - Specialty certification, AWS Certified Solutions Architect – Associate, or other relevant cloud certifications
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