Hybrid AI Engineering Specialist – Level 1

at AstraZeneca

• Job title: AI Engineering Specialist – Level 1
• Job type: Full Time
• Experience level: Senior, Lead
• Salary: Not specified
• Degree requirement: Bachelor's Degree
• Tech skills: AWS, Azure, Cloud, Google Cloud Platform, Python, PyTorch, Scikit-Learn, SQL, Tensorflow
• Location requirements: Hybrid, Chennai, India

About the role

• Senior Data Scientist leading data science and AI initiatives at AstraZeneca. Collaborating with global teams to transform healthcare delivery using advanced machine learning techniques.

Responsibilities

• Build, develop, and lead a team of high-performing Data Scientists
• Coordinate with cross-functional teams including Data Science & AI, Commercial, Medical, and IT globally
• Research and apply the latest ML algorithms with a focus on Generative AI techniques for content creation and data augmentation
• Apply ML models, feature engineering, and interpret model outcomes for business stakeholders
• Integrate structured and unstructured data into knowledge bases
• Design and create AZ knowledge graph
• Collaborate with data teams to demonstrate data science for research questions
• Partner with Commercial teams to build scalable data science solutions using Generative AI
• Drive collaborations with local data science companies
• Integrate data to build personalized patient journeys using LLMs and Diffusion Models
• Fine-tune LLMs and vision models for commercial problems
• Develop strategies for responsible use of Generative AI, including bias detection
• Optimize LLM performance through prompt engineering techniques

Requirements

• BS (or equivalent experience) in mathematics, computer science, engineering, physics, statistics, computational sciences, or related quantitative discipline
• Approximately 8-10 years of experience in core ML and AI projects
• Prior experience/understanding with 3-5 years' experience in foundational tools
• Python
• Jupyter notebook
• Scikit-learn
• SQL
• StreamLit
• Amazon Bedrock
• Jumpstart
• OpenAI
• Langchain
• LlamaIndex
• Good knowledge of cloud platforms (GCP, Azure, AWS)
• Deep Learning tools: Pytorch/Tensorflow, HuggingFace
• Classical methods including classification and regression algorithms like k-means clustering, support vector machines, random forests
• Fully Connected Architecture, Convolutional Networks, RNN/LSTM
• In-depth knowledge of LLMs like GPT, Claude, Gemini, Falcon, LLAMA
• Large pre-trained image models like Inception, Mobilenet, YOLO; generative image models like Stable Diffusion
• Experience with models/frameworks for text generation, image synthesis, data augmentation
• Ability to design and optimize prompts for LLMs

Benefits

• In-person working gives us the platform we need to connect, work at pace and challenge perceptions
• Dynamic environment fosters collaboration among the brightest minds