Associate Principal AI Scientist

AstraZeneca • Durham, NC

23h • Hybrid

About The Position

This role at AstraZeneca involves driving innovation in agentic AI, multi-agent systems, and digital twins within a global, science-led biopharmaceutical company focused on discovering, developing, and commercializing prescription medicines for serious diseases. The company emphasizes a hybrid work model, requiring a minimum of three days per week in the office to foster collaboration and bold thinking, while also respecting individual flexibility. AstraZeneca is committed to embracing change, trialing new solutions with patients and business in mind, and leveraging technology to deliver medicines quickly, affordably, and sustainably. The environment is digitally-enabled, impacting all parts of the business from robotic process automation to machine learning. The company fosters an inclusive and diverse culture, believing that innovation stems from diverse perspectives and a workforce empowered to challenge conventional thinking. They are dedicated to being a Great Place to Work, empowering employees to push scientific boundaries, embrace differences, and contribute to global healthcare and sustainability challenges. AstraZeneca offers a commitment to lifelong learning, growth, and development, aiming to help colleagues realize their full potential and make a significant difference in medicine, for patients, and society.

Requirements

• Min Bachelor´s degree in computer science, data science, artificial intelligence, machine learning or related fields.
• At least 3 years of experience in Deep Learning and ML.
• Excellent coding skills in languages such as Python, R.
• Hands-on industrial experience designing multi-agent patterns, digital twins and experience with agentic AI design patterns, reinforcement learning.
• Extensive industrial experience with AI and ML frameworks like TensorFlow, PyTorch.
• Hands-on experience with GenAI orchestration frameworks such as LangGraph, CrewAI.
• Hands-on experience with reinforcement learning libraries such as OpenAI Gym, Ray RLlib, or Stable Baselines.
• Hands-on industrial experience with applied machine learning domains such as deep learning, NLP, GenAI.

Nice To Haves

• Contributions to open-source projects.
• Strong publication record in the field of AI.
• Experience designing multi-agent systems in the pharmaceutical sector.
• Experience delivering machine learning projects with applications in pharmaceutical development, chemical engineering or chemistry.
• Experience with one or more of the following applied machine learning domains such as transfer learning, federated learning, few/zero shot learning, meta learning, explainable AI.

Responsibilities

• Drive innovation in agentic AI, multi-agent systems, and digital twins, exploring new methodologies and applications.
• Design, implement, and optimize algorithms for autonomous decision-making, coordination, and policy learning among agents and digital twins using techniques like Markov Decision Processes (MDPs), Partially Observable MDPs (POMDPs), and multi-agent reinforcement learning (MARL).
• Evaluate agent performance in the context of decision making, collaboration, competition, uncertainty.
• Collaborate with cross-functional teams ensuring knowledge transfer to IT engineering teams for IT solution builds and deployment.
• Keep pace with industry advancements by reviewing academic papers and attending conferences.
• Publish findings in peer-reviewed journals and represent the company at scientific forums.
• Communicate technical concepts and results to technical and non-technical audiences.

Benefits

• commitment to lifelong learning, growth and development for all
• inclusive and equitable environment where people belong
• empowered to push the boundaries of science, challenge convention and unleash your entrepreneurial spirit
• embrace differences and take bold actions to drive the change needed to meet global healthcare and sustainability challenges
• help you realise the full breadth of your potential

What This Job Offers

• Job Type: Full-time
• Career Level: Senior
• Number of Employees: 5,001-10,000 employees