Principal Machine Learning Engineer - Forecasting

Career Category

Engineering

ABOUT AMGEN

Amgen harnesses the best of biology and technology to fight the world's toughest diseases, and make people's lives easier, fuller and longer. We discover, develop, manufacture and deliver innovative medicines to help millions of patients. Amgen helped establish the biotechnology industry more than 40 years ago and remains on the cutting-edge of innovation, using technology and human genetic data to push beyond what is known today.

ABOUT THE ROLE

We are seeking a Principal Machine Learning Engineer to join the Forecasting team within the AI & Data Science organization. As a principal technical leader, this role will set technical direction and design, build, deploy, and scale enterprise-grade machine learning, large language model, and agentic AI systems that power forecasting capabilities, uncertainty-aware decision support, scenario planning, and operational decision automation across Amgen.

This role blends deep machine learning engineering expertise, modern AI systems architecture, and product-minded delivery. The Principal Machine Learning Engineer will solve highly ambiguous problems, identify high-impact automation opportunities, and translate advanced forecasting, predictive analytics, LLM-powered applications, and AI agent patterns into reliable, governed production solutions that support critical business processes and help Amgen deliver on its "every patient, every time" mandate.

The role is well suited to a hands-on technical leader who has shipped mission-critical AI/ML systems to production, understands the practical challenges of MLOps, and can operate effectively across engineering, data science, product, operations, commercial, manufacturing, supply chain, and senior stakeholder groups.

ABOUT THE TEAM

The Forecasting team within AI & Data Science is a cross-functional team focused on building AI-native forecasting, simulation, and decision-support capabilities for Amgen. The team partners closely with business, operations, and scientific stakeholders to understand enduring planning challenges, prototype solutions quickly, measure impact rigorously, and deploy reliable systems that inform real business decisions.

Our charter is to identify high-value forecasting and decision automation opportunities, build scalable AI/ML products that can support them reliably, and continuously improve these systems based on real-world performance, user adoption, forecast quality, and measurable business value.