Principal Machine Learning Engineer

<h2><b>Career Category</b></h2>Information Systems<h2></h2><h2><b>Job Description</b></h2><p><span>The AI/ML Lead will head Amgen’s AI/ML practice within the Innovation Lab, driving the development, validation, and deployment of machine learning and GenAI solutions across R&amp;D, Manufacturing, and Commercial domains.</span></p><p></p><p><span>This role requires strong technical depth, leadership skills, and a deep understanding of responsible AI frameworks within regulated environments.</span><br /> </p><p><b>Key Responsibilities</b></p><ul><li>Lead AI/ML strategy and implementation across multiple PoDs in the Innovation Lab.</li><li>Translate Amgen’s business objectives into data-driven AI/ML initiatives.</li><li>Define architecture, standards, and best practices for model design, training, and validation.</li><li>Oversee MLOps and CI/CD integration to enable scalable model deployment.</li><li>Guide the team on data preparation, feature engineering, and experimentation.</li><li>Review and approve model validation reports, metrics, and explainability artifacts.</li><li>Ensure compliance with Responsible AI, GxP, and privacy frameworks.</li><li>Collaborate with SMEs and Data Governance leads to align models with business and ethical objectives.</li><li>Mentor engineers, fostering innovation and technical excellence.</li></ul><p></p><p><b>Required Qualifications</b></p><ul><li>10–15 years of experience in data science or machine learning engineering.</li><li>Proven leadership in AI/ML project delivery and technical governance.</li><li>Expertise in Python, TensorFlow, PyTorch, Scikit-learn, or similar ML frameworks.</li><li>Experience with MLOps, MLflow, Databricks, and AWS SageMaker.</li><li>Strong grounding in model lifecycle management and validation documentation.</li><li>Excellent analytical, communication, and cross-functional collaboration skills.</li></ul><p></p><p><b>Preferred Skills</b></p><ul><li>Experience with GenAI / LLM architectures (LangChain, OpenAI APIs, Hugging Face).</li><li>Prior exposure to pharma, biotech, or life sciences R&amp;D.</li><li>Certification in Machine Learning / Data Science / AWS AI Specialist.</li><li>Familiarity with data privacy regulations (HIPAA, GDPR) and ethical AI standards.<br /> </li></ul><p></p><p style="text-align:inherit"></p><p style="text-align:inherit"></p><p style="text-align:inherit"></p>.