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Director – AI and Machine Learning
Amgen. Own an asset-agnostic portfolio turning human multi-omics, imaging, biomarker, and clinical data into insights for clinical drug development and regulatory evidence generation .
Core Competencies
Role fitCore Competencies
Use this summary to align your resume positioning with the role.
Demonstrates expertise in AI and machine learning methods for clinical drug development, with a strong focus on integrating multimodal human data and leading cross-functional teams. Proven ability to establish scalable AWS-based computing capabilities and drive organizational change in scientific and technical environments.
Highest-signal resume keywords
AI/ML ExperienceLeadership ExperienceComputational Biology ExpertiseAWS Infrastructure FamiliarityTranslational Analytics Delivery
ATS Keywords
Tailor your resumeApplicant Tracking System Keywords
Tip: use these terms in your resume and cover letter to boost ATS matches.
Hard Skills
Machine LearningDeep LearningStatistical AnalysisData IntegrationModel DevelopmentPharmacodynamic AnalysisPatient StratificationQuantitative ScienceBioinformaticsComputational Methods
Soft Skills
Team ManagementStrategic CommunicationCollaborationCoachingChange Leadership
Tools & Technologies
AWSCodexAI-Assisted DevelopmentMLOpsAnalytical Environments
Industry Keywords
Clinical Drug DevelopmentMulti-OmicsBiomarkersRegulatory EvidenceTranslational AnalyticsHuman Study DataScientific PublicationsQuality PracticesData LineageVersion Control
Tech Stack
Tools & technologiesAWSCloud
About the role
Key responsibilities & impact- Own an asset-agnostic portfolio turning human multi-omics, imaging, biomarker, and clinical data into insights for clinical drug development and regulatory evidence generation
- Set the strategy for shared AI and machine learning capabilities across therapeutic areas
- Translate scientific priorities into roadmaps for methods, platforms, and analytical products
- Partner with computational biology leaders and program-facing scientists to integrate capabilities into development workflows
- Lead the architecture and evolution of the analytics stack, including data integration, workflows, model development, evaluation, deployment, and interpretation
- Partner with technology, data engineering, security, and infrastructure teams to deliver scalable AWS-based computing and AI capabilities
- Establish reusable software, workflows, and standards for reproducibility, version control, testing, documentation, data lineage, and operations
- Lead statistical, machine learning, deep learning, and AI methods integrating multimodal human-study data
- Develop approaches for patient stratification, response prediction, pharmacodynamic analysis, and mechanism-of-action studies
- Direct cross-study and cross-asset analyses supporting translation and reverse translation
- Identify evidence gaps and evaluate external human datasets for acquisition, licensing, and internalization
- Lead agentification of analytical workflows using AI assistants and coordinated agents
- Automate validation, consistency checks, and QC triage with traceable expert review
- Establish evaluation and monitoring for scientific accuracy, reliability, reproducibility, tool use, and human oversight
- Embed privacy, access controls, provenance, model documentation, and fit-for-purpose quality practices
- Partner with biostatistics, clinical development, precision medicine, regulatory, safety, medical, and quality teams
- Enable traceable analyses for clinical decisions, regulatory submissions, publications, and scientific communications
- Manage, coach, and develop a scientific and technical team
- Strengthen AI fluency across multidisciplinary scientific and technical teams
- Lead adoption of new tools and working practices and communicate strategy, results, investment needs, and trade-offs
Requirements
What you’ll need- Doctorate degree and 4 years of relevant experience overall in computational biology, bioinformatics, quantitative science, data science, machine learning, or related fields; OR Master’s degree and 8 years of relevant experience; OR Bachelor’s degree and 10 years of relevant experience
- At least 4 years of experience directly managing people and/or leadership experience leading teams, projects, programs, or directing the allocation of resources
- Demonstrated AI/ML experience, including development, evaluation, and delivery of computational methods or capabilities addressing substantive scientific problems
- Recognized scientific eminence demonstrated by a sustained record of influential peer-reviewed publications and contributions advancing methods or scientific practice
- Experience analyzing or integrating complex human multimodal data, including multi-omics, imaging, clinical biomarkers, or clinical outcomes
- Experience delivering translational analytics in clinical drug development
- Familiarity with Codex, AI-assisted development, and AI-agent development and orchestration
- Familiarity with AWS infrastructure and cloud-based analytical environments
- At least 15 years of relevant experience overall is preferred
- PhD in a relevant computational, quantitative, engineering, or biomedical discipline is preferred
- Experience with modern software engineering, MLOps, model evaluation, and enterprise AI systems
- Experience leading organizational change and multidisciplinary technology adoption
- Sponsorship for this role is not guaranteed
Benefits
Comp & perks- A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions
- Group medical, dental and vision coverage
- Life and disability insurance
- Flexible spending accounts
- A discretionary annual bonus program
- Stock-based long-term incentives
- Award-winning time-off plans
- Flexible work models where possible
- Career development opportunities
- Work/life balance support