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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.
Job Responsibility:
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
Master’s degree and 8 years of Artificial Intelligence/ Machine Learning experience
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 have:
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
What we offer:
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