Hiring.Camp

Agentic AI Scientist

AstraZeneca

·

Jun 9, 2026

Location
Durham, NC,US, US
Workplace
Remote, Hybrid
Type
Full-time
Department
Education
Seniority
Senior
Experience
3+ years
Education
PhD
Category
Engineering
Environment
Office
Source
Eightfold

Overview

As an Associate Principal AI Data Scientist at AstraZeneca, you will contribute to cross-functional pharmaceutical development projects, focusing on agentic AI, multi-agent systems, and digital twins. You will design and optimize algorithms, collaborate with global teams, and publish findings. The role requires a PhD in a relevant field, 3+ years of experience in deep learning and ML, and proficiency in Python, R, and AI frameworks.

Description

Are you a driven Data Scientist with a robust foundation in traditional data science methods and a passion for Agentic AI, and human-in-the-loop (HITL) multi-agent systems? If so, an exciting opportunity awaits you at AstraZeneca!

We are looking for Associate Principal AI Data Scientists eager to utilize their expertise in these advanced technologies 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).

### Work Modality: Hybrid (3 days office and 2 remote)

Accountabilities:

  • 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.

Essential skills/Experience:

  • 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.

Desirable skills/experience:

  • 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.

When we put unexpected teams in the same room, we unleash bold thinking with the power to inspire life-changing medicines. In-person working gives us the platform we need to connect, work at pace and challenge perceptions. That's why we work, on average, a minimum of three days per week from the office. But that doesn't mean we're not flexible. We balance the expectation of being in the office while respecting individual flexibility. Join us in our unique and ambitious world.

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.

Ready to make a difference? Apply now to join our team!

Date Posted

09-jun-2026

Closing Date

06-jul-2026

Our mission is to build an inclusive environment where equal employment opportunities are available to all applicants and employees. In furtherance of that mission, we welcome and consider applications from all qualified candidates, regardless of their protected characteristics. If you have a disability or special need that requires accommodation, please complete the corresponding section in the application form.

Skills

PythonMachine LearningDeep LearningNLPTensorFlowPyTorchData ScienceGitHub

Languages

English

Remote Scope

USA

About AstraZeneca

AstraZeneca is a global biopharmaceutical company focused on discovering, developing, and delivering life-changing medicines.

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