Associate Director, AI Engineering for Discovery
AstraZeneca · Barcelona, Spain · Global
Software Engineering
Remote
physician
Demand88
Career growth88
Healthcare fit35
Remote potential55
5-year outlook
Likely strong long-term compensation growth because senior AI/ML engineering leadership in pharma is a scarce, high-value skill set. Exact figures depend on location, total rewards structure, and whether the role remains technical versus people-management focused.
Clinical license
Not required
Applicant reach
narrow
Seniority
lead
Employment type
full-time
Date found
2026-11-05
Intelligence details
Flexible work details
- Engagement type
- Permanent
- Hours
- Full-time
- Profession fit
- physician
Eligibility, licensing, and location restrictions can change. Always confirm details on the source posting before applying.
Why this is worth applying to
Only clinicians with substantial software engineering and production ML experience should consider this; it is a senior technical leadership role in pharma AI, not a transition-friendly non-clinical entry point.
Who should apply
Physician-scientists or healthcare graduates with strong production ML/software engineering backgrounds, especially those with cloud, MLOps, distributed training, and cross-functional scientific collaboration experience.
CV angle
Frame clinical or scientific domain knowledge as context for translating scientific needs into technical solutions, while emphasizing real software engineering, ML production deployment, MLOps, cloud-native delivery, distributed training, and technical leadership. Do not overstate clinical credentials as engineering experience.
Skills to highlight
- Python and scientific ML libraries such as PyTorch, NumPy, and Pandas
- Production AI/ML system design and deployment
- Distributed training and inference optimization
- CI/CD, DevOps, GitOps, and MLOps automation
- Cloud-native application deployment on AWS, GCP, or Azure
- Kubernetes and infrastructure as code
- Technical leadership, mentoring, and architecture decisions
- Responsible AI, governance, security, and reproducibility
Role summary
Senior AI engineering leader at AstraZeneca responsible for building scalable, reproducible AI/ML platforms and products for drug discovery, mentoring engineers, and setting engineering standards across cloud and on-premises environments.
We publish our own intelligence summary, never the full job description. Always confirm details with the employer when you apply.