Responsibilities

• Own small to medium components of machine learning systems from technical designthrough implementation and delivery
• Translate technical requirements into high-quality, maintainable code and deliver workstreamsaccording to plan
• Build and maintain data pipelines and feature engineering workflows to support machinelearning and AI solutions
• Design, train, evaluate, and refine machine learning models with minimal supervision, applyingsound statistical and engineering practices
• Implement ML solutions that can be deployed into production environments as microservices,APIs, batch jobs, or streaming components
• Support production monitoring efforts by helping define and implement metrics for modelperformance, data drift, anomalies, and retraining triggers
• Collaborate with Data Engineers, Software Engineers, Data Scientists, Product partners, andbusiness stakeholders to deliver project objectives
• Understand system design, data models, and technical artifacts well enough to contribute toimplementation decisions and tradeoffs
• Follow governance, documentation, coding, and source control standards consistently
• Demonstrate flexibility and proactively support teammates with day-to-day responsibilities asneeded
• Clearly document and communicate work progress, technical decisions, and outcomes totechnical and non-technical audiences