Machine Learning Engineer

Senior Machine Learning Engineer - Computational Science & Informatics (CSI) We are looking for a Senior Machine Learning Engineer with a strong technical background rooted in fundamental computer science and database management. The role involves leading technical decisions, driving long-term planning, architecture, and design of core ML and Data Platform initiatives, and providing robust infrastructure and tooling for Data Scientists. Key Responsibilities * Act as the central technical liaison between project stakeholders and the Data Science team, taking full ownership of integrating and deploying algorithms and machine learning models into production workflows. * Design, build, and scale cloud-native and hybrid data and machine learning platforms (MLOps) tailored to the complex, evolving needs of our established Data Science team. * Plan, architect, and develop long-term enterprise tooling and infrastructure for internal use to accelerate and streamline ML model research, training, and evaluation. * Take responsibility for the end-to-end software and data architecture within Data Science initiatives, independently driving the specification, implementation, and testing of complex technical assignments. * Serve as a technical lead and subject matter expert, gathering requirements from data-focused profiles to continuously improve the ML platform while mentoring peers to foster a culture of engineering excellence. Qualifications & Skills * A degree in Computer Science, Software Engineering, or a closely related technical field. * Extensive professional experience in software engineering with Python, including a deep understanding of Application Architecture and Design Patterns. * Strict adherence to coding best practices (TDD, ATDD), rigorous testing strategies, and proper version control. * Strong understanding of complete ML workflows and hands-on experience provisioning the infrastructure required to support them. * Significant experience with various storage technologies, understanding their specific trade-offs (Relational Databases, No-SQL Databases, Object Storage). * Solid knowledge and practical experience with HPC (High-Performance Computing) and AWS-based data engineering and analytics solutions. * Deep familiarity with the Python data ecosystem (NumPy, Pandas, Scikit-learn), proficiency in Linux environments, and hands-on experience with modern data integration, ETL, and MLOps tools. * Domain knowledge or strong interest in life sciences (Sequencing, PCR, Bioinformatics, or digital healthcare) - nice to have. * Experience building, deploying, or working with Large Language Models (LLMs) and agentic systems - nice to have. * Official Cloud certifications (AWS Certified Solutions Architect - Professional or equivalent) - nice to have. * Proven experience working successfully within large, globally distributed, or international enterprise environments - nice to have. Location & Logistics This is an on-site