Amgen is looking to solve real-world problems in the healthcare industry using Reinforcement Learning from Human Feedback (RLHF) and related reinforcement learning approaches to serve patients better and faster.
Requirements
- Deep, hands-on expertise in Reinforcement Learning from Human Feedback (RLHF) and/or advanced reinforcement learning, including reward modeling, policy optimization, exploration strategies, and offline/online evaluation.
- Demonstrated experience deploying RLHF or RL systems into production for real-world applications (e.g., large language models, recommendation systems, decision support tools, or workflow automation), ideally in healthcare, life sciences, or other regulated domains.
- Strong background in modern machine learning and deep learning, with practical experience in Python and frameworks such as PyTorch or TensorFlow, and familiarity with LLM ecosystems and tooling.
- Experience driving sophisticated, cross-functional initiatives, collaborating with non-technical stakeholders (e.g., physicians, scientists, commercial leaders, compliance, legal) and translating needs into impactful AI solutions.
- Strong ability to communicate complex technical topics simply, tailoring content to senior executives and non-technical audiences; well-versed in data and model storytelling, including risks, assumptions, and limitations.
- Experience working with large-scale data and cloud ecosystems (e.g., Azure, Databricks, Snowflake, or similar), and partnering with data engineering or platform teams to build robust pipelines and experimentation platforms.
- Demonstrated understanding of responsible AI, safety, and governance, especially in the context of RLHF and LLMs (e.g., bias, robustness, transparency, and guardrail design).
Responsibilities
- Lead the design and development of RLHF systemsincluding reward modeling, policy optimization, safety and alignment mechanisms, and evaluation frameworks for large language models and other AI systems.
- Drive hands-on technical execution, particularly for high-impact projects, reviewing architectures, experimentation plans, and code, and helping the team navigate scientific and engineering trade-offs.
- Establish best-practice pipelines for human feedback, partnering closely with internal customer teams to define feedback protocols, annotation quality standards, and governance for RLHF data.
- Define and track success metricsfor RLHF systems, balancing offline and online evaluation, A/B tests, safety and robustness criteria, and business or scientific outcomes.
- Collaborate across Amgenleaders to ensure RLHF solutions are aligned with strategy, compliant with policy, and integrated into real workflows.
- Partner with Data, Platform and Technology teamsto ensure that RLHF workloads are supported by scalable data platforms, model hosting, experimentation infrastructure, and MLOps best practices.
- Champion responsible and compliant AI, working with Legal, Compliance, and Information Security to implement governance around human feedback, data usage, model behavior, transparency, and risk management in a regulated environment.
Other
- Doctorate degree and 3 years of Computer Science, IT or related field experience
- Masters degree and 5 years of Computer Science, IT or related field experience
- Bachelors degree and 7 years of Computer Science, IT or related field experience
- Associates degree and 12 years of Computer Science, IT or related field experience
- High school diploma / GED and 14 years of Computer Science, IT or related field experience
