Sr. ML Engineer

Overview

Sr. Machine Learning Engineer role building and modelling digital products and platforms that bring Amgen's AI/ML and GenAI solutions to life for discovery, manufacturing, commercial analytics and corporate functions.

What you'll do

• Build and model digital products and platforms that bring Amgen's AI/ML and GenAI solutions to life.
• Collaborate with Amgen's Technical Architect, Product Manager, UX designers and Back-end engineers to design secure, scalable and user-centric products.
• Collaborate with cross-functional teams, including Data Architects, Business SMEs and Technical Architect, to understand requirements and design solutions that meet business needs.
• Experiment with large language models (LLM), artificial intelligence (AI) for code, Generative AI, Foundational Models, and supervised and unsupervised learning.
• Explore new tools and technologies that will help rapid development of solutions.
• Participate in sprint planning meetings and provide estimations on technical implementation.
• Embed responsible-AI and security-by-design controls.

What you'll need

• Strong experience with statistics and machine learning, including deep learning, natural language processing (NLP).
• Experience in building cloud-scale systems and working with open-source stacks for data.
• Experience in Generative AI, Foundational Models, LLMs, Feature Engineering, Selection & Extraction, BI & Automation, Predictive Modelling, Data Visualization, CNN, RNN, GNN, Transformers, Exploratory Data Analysis and Causal AI.
• Familiarity with Python packages (PyTorch, TensorFlow, Hugging Face, Scikit-learn, Pandas, NumPy, Matplotlib, Cloud Vision API, RAG, TensorBoard, OpenCV, NLTK) and programming languages (C, C++, Java, CUDA, SQL, NoSQL, PHP, HTML, JS, CSS etc.).
• 6–12 years of experience in Data Science (e.g. managing structured and unstructured data, applying statistical techniques and reporting results).
• Doctorate, Master's or Bachelor's in Computer Science, Data Science, Mathematics, Statistics, Econometrics, Economics, Operations Research, or a related field.
• Leverage cloud platforms (AWS preferred) to build scalable and efficient solutions.
• Strong background in Deep Learning, Machine Learning, NLP, Data Mining.
• Excellent communication and stakeholder management skills.

Nice to have

• Prior exposure to pharma / life sciences AI environments.
• Strong understanding of Responsible AI and model validation principles.

Details

• Location: Hyderabad, India.