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 810 years of experience in AI/ML, or
- Bachelor's degree and 1014 years of experience, or
- Diploma and 1418 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 workflows
- Experience 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.
