SrMachineLearningEngineer

## **Career Category** Engineering ## ## **Job Description** # Position Overview The GCF5 Sr Machine Learning Engineer is the senior technical leader for the Agentic & ML Platform pillar. They define and socialize platform standards and patterns, lead multi-team delivery, mentor GCF4 engineers, and translate scientific needs into scalable ML/agentic platform designs. They own pillar-level adoption, reliability, and SLA/SLO outcomes, and influence cross-team engineering quality. This role reports to the GCF7 leader and partners closely with peer GCF5 domain leads across SCIP to ensure cohesive, scalable platform evolution. # Core Responsibilities * Own the ML and agentic platform technical roadmap within SCIP. * Design and operationalize reusable ML/agentic infrastructure components enabling repeatable deployment. * Define evaluation harnesses and model release gates. * Establish monitoring, rollback, and observability practices for production ML systems. * Implement guardrails and operational controls for safe agentic workflows. * Define reproducibility standards and artifact versioning practices. * Lead architecture reviews for ML platform evolution. * Mentor engineers and elevate ML engineering rigor. * Partner with research stakeholders to translate AI use cases into scalable platform capabilities. # Core Competencies * Deep expertise in the assigned pillar (Agentic & ML Platform) (Agentic‑ML) with evidence of standard‑setting and reuse. * Systems design at scale (ML); performance, security, and observability fundamentals. * Product/engineering thinking: road mapping, prioritization, and outcome‑oriented delivery. * Stakeholder influence across science, engineering, and governance forums; crisp written/verbal communication. # Core Success Measures * Adoption rate of standardized ML platform components. * Evaluation coverage across supported ML use cases. * Reduction in model regressions and production ML incidents. * Time-to-deploy new ML use cases. * Reproducibi