Agentic AI Scientist

AstraZeneca • Gaithersburg, MD

3d • Hybrid

About The Position

An exciting opportunity awaits you at AstraZeneca! We are looking for Associate Principal AI Data Scientists eager to utilize their expertise in Agentic AI, human-in-the-loop (HITL) multi-agent systems, and digital twins to revolutionize our drug development processes. In the Pharmaceutical Technology and Development (PT&D) department, you will be a key player in transforming molecules into groundbreaking medical treatments. PT&D leads the charge in developing cutting-edge synthetic routes, drug formulations and delivery technologies, ensuring our products are effective, safe, and of the highest quality. Your role involves contributing data science expertise into cross functional global pharmaceutical development projects in support of transforming the way we deliver medicines to patients. You'll play a pivotal role in shaping our AI strategy and driving the co-development of sophisticated HITL multi-agent systems. We are hiring two candidates for this position, and the roles will be based at our dynamic site in Durham (USA).

Requirements

• PhD 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. If you meet these criteria, please highlight merged GitHub PRs in your application.
• 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

• AstraZeneca is a place where change is embraced, and new solutions are trialed with patients and business in mind.
• Here, technology is a key lever for delivering medicines quickly, affordably, and sustainably.
• Our diverse workforce is united by curiosity, sharing learnings to scale fast.
• Be part of a digitally-enabled environment that impacts all parts of the business—from robotic process automation to machine learning for quality batches—while contributing to society and the planet.

What This Job Offers

• Job Type: Full-time
• Career Level: Principal
• Education Level: Ph.D. or professional degree