Director, AI/ML
AstraZeneca · Bangalore, India · Global
Clinical Data Science
–
physician
Demand88
Career growth85
Healthcare fit28
Remote potential65
5-year outlook
Senior AI/ML leadership roles in large pharma tend to command premium compensation, with exact pay dependent on location, level, and total rewards structure. Five-year outlook is strong for leaders with production GenAI and agentic AI experience, though expectations will rise as the field matures.
Clinical license
Not required
Applicant reach
narrow
Seniority
senior
Employment type
full-time
Date found
2026-11-09
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
Worth considering only for clinicians who already have deep, production-grade ML/AI leadership experience and want to lead pharma commercial AI strategy. Most clinicians without 12+ years of data science/ML experience should treat this as a stretch or long-term target rather than an entry point.
Who should apply
Physician-data scientists, clinician-ML leaders, pharmacist informatics leaders, or healthcare graduates with extensive industry AI/ML experience, especially those who have built production LLM or agentic AI systems and led cross-functional technical teams.
CV angle
Frame real healthcare experience as domain context while foregrounding verifiable ML/AI delivery: production model deployment, LLM and agentic system architecture, evaluation/observability standards, model optimization, responsible-AI governance, and cross-functional leadership with commercial, medical, and engineering partners. Do not present clinical credentials as a substitute for the required 12+ years of ML/data science experience.
Skills to highlight
- Generative AI and LLM application development
- Agentic AI and multi-agent system design
- ML/AI architecture and technical roadmap setting
- Model evaluation, observability, and production monitoring
- Fine-tuning, distillation, and cost/latency optimization
- Cross-functional leadership and stakeholder translation
- Responsible AI, governance, and guardrails
- Mentoring senior data scientists and ML engineers
Role summary
A senior AI/ML leadership role at AstraZeneca focused on defining the technical vision and architecture for traditional ML, generative AI, and agentic AI across commercial and medical data. The position combines hands-on technical direction, production AI standards, evaluation and observability, model optimization, governance, and cross-functional influence with Commercial, Medical, and Technology partners.
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