Associate Director -Gen AI/ML(MLops, Gen AI & Azure)

Major accountabilities: Solution Design: Architect scalable GenAI solutions for drug discovery, medical writing automation, clinical trials, regulatory submissions, and real-world evidence generation.LLM Development & Optimization: Work with data scientists and ML engineers to develop, fine-tune, and optimize large language models (LLMs) for life sciences applications, such as scientific literature analysis, regulatory intelligence, and patient engagement.AI Infrastructure: Design GenAI solutions leveraging cloud platforms (AWS, Azure, GCP) or on-premises infrastructure while ensuring data security and regulatory compliance.MLOps & Deployment: Implement best practices for GenAI model deployment, monitoring, and lifecycle management within GxP-compliant environments.Compliance & Governance: Ensure GenAI solutions comply with regulatory standards (FDA, EMA, GDPR, HIPAA, GxP, 21 CFR Part 11) and adhere to responsible AI principles, including bias mitigation and exploitability.Performance Optimization: Drive efficiency in generative AI models, ensuring cost optimization and scalability while maintaining data integrity and compliance.Stakeholder Collaboration: Work with cross-functional teams, including platform teams, engineering teams from various supplier/vendors to align GenAI initiatives with enterprise and industry-specific requirements.Research & Innovation: Stay updated with the latest advancements in GenAI, multimodal AI, AI agents, and synthetic data generation to incorporate emerging technologies into the company's AI strategy.Minimum RequirementsBachelor's or master's degree in computer science, AI, Data Science, Bioinformatics, or a related field.Experience: 12+ years' experience in Big data, AI/ML development with at least 8 years in an AI Architect or GenAI Architect role in pharma, biotech, or life sciences.Technical Expertise:Strong proficiency in Generative AI, large language models (LLMs), multimodal AI, and deep learning for pharma applications.Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch, Hugging Face, LangChain, Scikit-learn, etc.).Experience with data engineering, ETL pipelines, and big data technologies (Spark, Kafka, Databricks, etc.).Knowledge of cloud AI services (AWS Bedrock, Azure OpenAI, Google Vertex AI).Lead the deployment of a Lightweight LLM in a Pharma SaaS PlatformMLOps & DevOps: Familiarity with CI/CD, containerization (Docker, Kubernetes), vector databases, and real-time model monitoring.Regulatory & Ethical AI: Understanding of AI governance, responsible AI principles, and compliance requirements for GenAI in pharma.Problem-Solving: Strong analytical and problem-solving skills with the ability to design innovative GenAI solutions for life sciences use cases.Communication & Leadership: Excellent communication skills to articulate GenAI strategies and solutions to technical and non-technical stakeholders

Novartis is a global healthcare company based in Switzerland that provides solutions to address the evolving needs of patients worldwide.