Sr Director- Reinforcement Learning

Amgen • Thousand Oaks, CA

2d • Hybrid

About The Position

Join Amgen’s Mission of Serving Patients At Amgen, if you feel like you’re part of something bigger, it’s because you are. Our shared mission—to serve patients living with serious illnesses—drives all that we do. Since 1980, we’ve helped pioneer the world of biotech in our fight against the world’s toughest diseases. With our focus on four therapeutic areas –Oncology, Inflammation, General Medicine, and Rare Disease– we reach millions of patients each year. As a member of the Amgen team, you’ll help make a lasting impact on the lives of patients as we research, manufacture, and deliver innovative medicines to help people live longer, fuller happier lives. Our award-winning culture is collaborative, innovative, and science based. If you have a passion for challenges and the opportunities that lay within them, you’ll thrive as part of the Amgen team. Join us and transform the lives of patients while transforming your career. Sr. Director- Reinforcement Learning What you will do Responsibilities Define enterprise RL roadmaps, landmarks, and success metrics; drive early hands-on prototypes as the capability matures . Architect simulation environments, reward structures, and training loops for scientific and operational RL use cases. Lead algorithmic innovation and technical decisions across model-based RL, policy gradient methods, and actor-critic architectures . Advance RL for scientific domains such as protein design, docking, and structural modeling; expand RL beyond R&D into Manufacturing, Supply Chain, and Commercial applications . Oversee data pipelines, curation, and feature engineering supporting RL experimentation and multi- modal model training. Guide RL pilots from proof-of-concept through production deployment, ensuring ML Ops rigor— versioning, automated testing, monitoring, and continuous training . Partner deeply with biology, engineering, platform teams, product teams, and enterprise AI groups to integrate RL into existing workflows and systems. Mentor and develop talent; drive innovation, safety, and scientific/engineering excellence. Evaluate emerging research, open-source frameworks, and frontier methods (e.g., multi-agent RL, RLHF, simulation-based optimization) for enterprise adoption . Communicate outcomes, technical decisions, and implications to leadership and key stakeholders.

Requirements

• Doctorate degree and 5 years of Artificial Intelligence/ Machine Learning experience OR Master’s degree and 8 years of Artificial Intelligence/ Machine Learning experience OR Bachelor’s degree and 10 years of Artificial Intelligence/ Machine Learning experience
• PhD or equivalent experience in ML, RL, or related fields.
• 10+ years AI/ML
• 5+ years reinforcement learning leadership.

Nice To Haves

• Proficient Python, PyTorch/TensorFlow, distributed training.
• Contributions to AlphaFold-like or large-scale scientific AI.
• Publications at NeurIPS , ICML, or ICLR.
• Biotech, pharma, or healthcare domain exposure.
• Familiarity with GxP , HIPAA, or FDA guidance.
• Experience leading AI Centers of Excellence.
• Patents or open-source RL contributions.
• Prior collaborations with academia or top AI labs

Responsibilities

• Define enterprise RL roadmaps, landmarks, and success metrics; drive early hands-on prototypes as the capability matures
• Architect simulation environments, reward structures, and training loops for scientific and operational RL use cases.
• Lead algorithmic innovation and technical decisions across model-based RL, policy gradient methods, and actor-critic architectures
• Advance RL for scientific domains such as protein design, docking, and structural modeling; expand RL beyond R&D into Manufacturing, Supply Chain, and Commercial applications
• Oversee data pipelines, curation, and feature engineering supporting RL experimentation and multi- modal model training.
• Guide RL pilots from proof-of-concept through production deployment, ensuring ML Ops rigor— versioning, automated testing, monitoring, and continuous training
• Partner deeply with biology, engineering, platform teams, product teams, and enterprise AI groups to integrate RL into existing workflows and systems.
• Mentor and develop talent; drive innovation, safety, and scientific/engineering excellence.
• Evaluate emerging research, open-source frameworks, and frontier methods (e.g., multi-agent RL, RLHF, simulation-based optimization) for enterprise adoption
• Communicate outcomes, technical decisions, and implications to leadership and key stakeholders.

Benefits

• A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts
• A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan
• Stock-based long-term incentives
• Award-winning time-off plans
• Flexible work models, including remote and hybrid work arrangements, where possible

What This Job Offers

• Job Type: Full-time
• Career Level: Director
• Education Level: Ph.D. or professional degree
• Number of Employees: 5,001-10,000 employees