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Associate – AI/ML Innovation Engineer
Amgen
Hyderabad, IND
Full-time
Entry · 1+ years experience
Onsite
Discovered 3 weeks ago
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ABOUT AMGEN
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.
Role Description
As an AI/ML Innovation Associate, you will help build next-generation AI-powered platforms that transform how commercial, contracting, and patient access strategies are designed and executed across the US Value & Access organization. Our AI portfolio includes AI copilots, intelligent contract systems, anomaly detection engines, and real-time decision platforms that directly impact how Amgen serves patients and partners.
In this role, you will work on production-grade AI systems, contributing to the development of scalable, intelligent solutions that integrate structured and unstructured data, power decision-making, and deliver measurable business impact. You will collaborate with senior data scientists, engineers, and business partners to bring cutting-edge GenAI, LLM, and ML solutions from prototype to production.
Roles & Responsibilities
- You will contribute to one or more of the following high-impact areas:
- AI Copilots & Agents : Build LLM-powered assistants, implement prompt engineering, Retrieval-Augmented Generation (RAG) pipelines, and agentic workflows and related applications
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