ROLE SUMMARY

As a core member of our AI/ML, Quantitative & Digital Sciences (AQDS) team, you will:

• Design, implement, and maintain full-stack applications that integrate advanced Machine Learning (ML) techniques with internal and external data sources.
• Develop and apply generative AI techniques using large language models (LLMs) to automate the generation of essential clinical trial documents.
• Collaborate with cross-functional teams to architect and develop scalable, cloud-native microservices and APIs for AI/ML tools aimed at optimizing patient recruitment, site selection, and clinical trial management, incorporating generative AI capabilities to streamline authoring workflows.
• Leverage modern front-end frameworks (e.g., React, Angular, Vue) to build intuitive user interfaces that provide real-time insights from ML models and facilitate decision-making for clinical operations, including AI-generated document review and customization.
• Work closely with DevOps and data engineering teams to streamline CI/CD pipelines, automate infrastructure as code (IaC), and ensure secure deployment of AI/ML models, including generative AI systems, across cloud environments (AWS, Google Cloud, Azure).
• Implement AI/ML models in full-stack systems, ensuring robust backend processing and efficient front-end data visualization.
• Engage with both internal and external stakeholders to continuously bring the latest advancements in generative AI, full-stack development, and AI/ML technologies to Pfizer, contributing to thought leadership through publications and presentations.

ROLE RESPONSIBILITIES

• Partner with key therapy areas (e.g., Immunology & Inflammation, Oncology, Internal Medicine) to identify scientific and technical challenges, define data pipelines, and implement full-stack solutions that leverage AI/ML methods, including generative AI models, to generate actionable insights and automate clinical trial documentation.
• Translate complex clinical data and analytics requirements into full-stack digital products, ensuring that development priorities align with the overall clinical development goals.
• Lead the end-to-end development of full-stack applications, from database schema design and API development to front-end user interfaces, ensuring seamless integration with AI/ML workflows and LLM-powered document generation systems.
• Supervise and guide the deployment of robust back-end services that support predictive and classification algorithms, as well as generative AI models, ensuring scalability, security, and performance.
• Develop and maintain dashboards and data visualization tools that provide clinical and operational teams with real-time analytics and insights driven by advanced ML models, while integrating tools for generating and reviewing AI-authored clinical trial documents.
• Maintain an active external network in the AI/ML, generative AI, and full-stack development communities, continuously monitoring state-of-the-art capabilities and evaluating their potential impact on Pfizer’s development teams.

QUALIFICATIONS

Basic Qualifications

• Bachelor’s degree in Computer Science, Software Engineering, Bioinformatics, Computational Biology, or a related technical discipline.
• Minimum of 2 years of experience in full-stack development in the pharma, biotech, or tech industry.
• Proficient in full-stack development, including back-end technologies (Node.js, Django, Flask) and front-end frameworks (React, Angular, Vue).
• Strong understanding of database technologies (SQL, NoSQL) and experience in designing RESTful APIs and microservices architectures.
• Experience with AI/ML model integration, including developing APIs to interface with ML models and building front-end components for real-time data visualization.
• Experience working with large language models (LLMs) for generative AI applications.
• Strong programming skills (Python, JavaScript, R) and familiarity with cloud technologies (AWS, Google Cloud, Azure).
• Experience working with CI/CD pipelines, containerization (Docker, Kubernetes), and infrastructure automation tools (Terraform, Ansible).
• Strong written and verbal communication skills with the ability to translate complex technical concepts for non-technical stakeholders.

Preferred Qualifications

• Master’s degree in a technical or scientific discipline (e.g., Computer Science, Computational Biology, Engineering).
• Hands-on experience with the full-stack development of clinical trial management systems, focusing on integrating AI/ML-driven insights into clinical workflows, and automating document generation through LLMs.
• Proven experience leading end-to-end clinicaldevelopment projects, particularly in Phases 2 and 3, from study design to regulatory submission.
• Experience with data engineering workflows, including ETL processes, data lakes, and scalable data architectures.
• Prior experience working with distributed teams across multiple time zones is a plus.

Please apply by sending your CV and a motivational letter in English

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