Sr Machine Learning Engineer

Key Responsibilities

• 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.

Basic Qualifications

• 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.

Preferred Qualifications

• 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.

EQUAL OPPORTUNITY STATEMENT

Amgen is an Equal Opportunity employer and will consider you without regard to your race, color, religion, sex, sexual orientation, gender identity, national origin, protected veteran status, or disability status.

We will ensure that individuals with disabilities are provided with reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.

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