Senior Machine Learning Engineer

4w1 month ago

Amgen

Hyderābād, IN · Full-time · INR 2,000,000 – INR 3,500,000

About this role

Amgen seeks a highly motivated Senior Machine Learning Engineer to design and develop scalable, secure, and reliable data pipelines that power generative AI solutions for the Manufacturing Applications Product Team. This role focuses on building production-grade GenAI and machine learning systems, including retrieval-augmented generation and agentic workflows.

Day-to-day, you will design, deploy, monitor, and optimize ML and GenAI applications for AI-enabled manufacturing solutions. You will define technical architecture and engineering standards across data engineering, ML, and platform capabilities, ensuring security and scalability.

You will partner with business stakeholders, product owners, and cross-functional teams to translate manufacturing challenges into production-ready AI solutions. Collaboration with experts in biology and technology is central, as Amgen harnesses cutting-edge innovation to fight the world's toughest diseases.

This role offers the opportunity to work at the intersection of data engineering, MLOps, and modern AI platforms. You will contribute to transformative projects that enable advanced analytics, automation, and decision support across manufacturing operations, making a tangible impact on patient lives.

Requirements

Proven experience designing and building production-grade ML and GenAI systems, including RAG and agentic workflows.
Deep expertise in data engineering with PySpark, Scala, and SQL on Databricks or similar distributed computing platforms.
Strong knowledge of MLOps practices and modern AI platforms for secure, scalable solution delivery.
Experience building end-to-end data pipelines for structured and unstructured data (databases, APIs, logs, documents, images).
Familiarity with vector databases, embeddings, and retrieval-augmented generation techniques.
Ability to define technical architecture and engineering standards for AI and data projects.
Proven track record partnering with business stakeholders to deliver production-ready AI solutions in a regulated industry.
Strong programming skills in Python and experience with cloud platforms (AWS, Azure, or GCP).

Responsibilities

Design, deploy, monitor, and optimize production-grade ML and Generative AI applications for AI-enabled manufacturing solutions.
Define technical architecture, engineering standards, and best practices across data engineering, ML, GenAI, analytics, and platform capabilities.
Partner with business stakeholders, product owners, and cross-functional teams to translate manufacturing challenges into secure, scalable, production-ready AI and data solutions.
Design, develop, and maintain complex ETL/ELT pipelines in Databricks using PySpark, Scala, and SQL for large-scale structured and unstructured data processing.
Build efficient ingestion, transformation, migration, and deployment pipelines across databases, APIs, logs, event streams, images, PDFs, documents, and third-party platforms.
Design and implement GenAI solutions including retrieval-augmented generation (RAG), embeddings, vector databases, agentic workflows, and tool-calling systems.