Senior Machine Learning Engineer, Forecasting

Job title: Senior Machine Learning Engineer, Forecasting

About the Role We are seeking a Senior Machine Learning Engineer, Forecasting to join the Forecasting team within the AI & Data organization. This role will design, build, deploy, and maintain scalable ML systems that power forecasting capabilities and uncertainty-aware decision support across Amgen, enabling multi-horizon planning and strategic decision-making.

What You'll Do

• Design, build, and maintain scalable machine learning systems and forecasting pipelines to support demand forecasting across near-, medium-, and long-term planning horizons.
• Productionize advanced statistical, Bayesian, and machine learning forecasting models, including training, validation, deployment, and lifecycle management.
• Build and optimize data pipelines, feature engineering workflows, and batch and real-time inference systems using large, complex datasets.
• Own the end-to-end ML engineering lifecycle, including solution design, prototyping, model integration, testing, deployment, monitoring, observability, and continuous improvement.
• Develop robust MLOps capabilities, including model versioning, CI/CD, automated retraining, performance monitoring, drift detection, and rollback strategies.
• Partner closely with data scientists and business stakeholders to operationalize forecasting, simulation, and scenario-analysis capabilities that support strategic decision-making.
• Establish and promote software engineering best practices, including code quality, documentation, reproducibility, and system reliability.
• Research and evaluate emerging tools, platforms, and methodologies in machine learning engineering, forecasting, and AI for potential application to business problems.

What We're Looking For

• 8+ years of experience in machine learning engineering, software engineering, or a related field, with a demonstrated track record of deploying production ML systems that deliver business value.
• Strong experience building and maintaining end-to-end ML pipelines and production systems for forecasting or other predictive modeling use cases.
• Expertise in model serving, and operationalizing probabilistic, Bayesian, or predictive models in production environments.
• Strong programming skills in Python and SQL, with experience using tools such as scikit-learn, PyTorch, TensorFlow, and orchestration or workflow tools for ML pipelines.
• Experience with cloud platforms, distributed data processing, containerization, and ML deployment patterns.
• Strong understanding of software engineering fundamentals, including system design, testing, performance optimization, and maintainability.
• Strong collaboration and communication skills, with the ability to work effectively across technical and non-technical teams.
• An intellectually curious self-starter who can take ambiguous problems and build scalable solutions from the ground up.

Nice to Have

• Experience building and deploying forecasting models for biotech/pharma use cases with knowledge of healthcare commercial concepts such as payer/provider dynamics, formulary access, and coverage.
• Experience partnering closely with data scientists to translate advanced statistical or machine learning models into reliable production services.
• Experience leveraging machine learning and forecasting systems in retail, consumer goods, supply chain, or manufacturing applications.
• Familiarity with model monitoring, explainability, and governance requirements in regulated or high-impact business environments.