Amgen is seeking a Principal AI / ML Engineer with deep expertise in multi-agent system design and agentic architectures to drive the next generation of enterprise AI innovation.
In this role, you will spearhead the development of scalable, secure, and intelligent agent-based AI / ML platforms , while mentoring teams, setting technical direction, and aligning AI strategies with business priorities.
You will serve as a hands-on technical leader in reinforcement learning (RL) , RLHF , active learning , and other agentic methodologies, playing a vital role in advancing Amgen's digital transformation and accelerating innovation in life sciences.
Key Responsibilities :
AI / ML Thought Leadership & Mentorship
- Mentor AI / ML engineers and data scientists in modern agent-based design patterns.
- Foster a culture of innovation and continuous learning in emerging AI fields.
Agent-Based System Development
Architect and deploy multi-agent AI systems that enhance decision-making, automation, and adaptive intelligence.Prototype and optimize reinforcement learning models and agentic frameworks.Strategic Framework Development
Define scalable and secure AI / ML frameworks for agentic infrastructure , focusing on enterprise-wide application.Create reusable blueprints, SDKs, and technical standards for multi-agent systems.Enterprise-Level Integration
Work cross-functionally with platform, product, and operations teams to embed intelligent agents into Amgen's core digital ecosystems.Translate business challenges into AI / ML agentic solutions aligned with corporate objectives.Innovation & Research
Drive R&D in cutting-edge AI disciplines such as RLHF, self-play, and decentralized intelligence.Evaluate and adopt new toolkits, methodologies, and agentic paradigms for Amgen's evolving AI stack.Performance, Quality & Compliance
Ensure AI solutions meet enterprise-grade requirements for scalability, security, and maintainability.Maintain rigorous documentation and testing practices to support auditability and future enhancements.Basic Qualifications :
Master's degree and 8–10 years of experience in AI / ML, orBachelor's degree and 10–14 years of experience, orDiploma and 14–18 years of progressive experience in AI, machine learning, and data science.Required Technical Expertise :
Proven track record in designing and implementing agent-based AI / ML systems .Deep knowledge of :Reinforcement learning (e.g., PPO, DQN, A3C)RLHF (Reinforcement Learning from Human Feedback)Active learning workflowsExperience with agent-based modeling frameworks (e.g., Rasa , PettingZoo , OpenAI Gym , or custom agentic environments).Strong skills in cloud-based ML platforms (e.g., AWS SageMaker, Azure ML, GCP Vertex AI).Proficient in languages and tools such as Python , TensorFlow , PyTorch , Ray RLlib , JAX .Preferred Qualifications :
Working knowledge of data privacy and security regulations relevant to AI (e.g., GDPR, HIPAA).Background in project leadership of complex AI systems.Experience authoring technical documentation and AI design artifacts at enterprise scale.Familiarity with life sciences, pharmaceutical, or regulated environments is a plus.Soft Skills & Leadership Competencies :
Visionary leadership with the ability to inspire and align cross-functional teams.Strategic mindset , able to bridge emerging AI capabilities with long-term business value.Strong communication and collaboration skills across technical and non-technical stakeholders.High adaptability to emerging technologies, with a passion for innovation and experimentation.Skills Required
Modeling Tools, Data Science, reinforcement learning, Artificial Intelligence, Machine Learning
