Sr. Specialist - AI/ML

As an AI Technical Specialist, you will play a key role in developing and implementing advanced AI solutions, working closely with suppliers and vendors to ensure successful rollout and integration

• Solution Development: Design and implement scalable Generative AI solutions for applications such as drug discovery, medical writing automation, clinical trials, regulatory submissions, and real-world evidence generation.
• LLM Development & Optimization: Collaborate with data scientists and ML engineers to develop, fine-tune, and optimize large language models (LLMs) for life sciences applications, including scientific literature analysis, regulatory intelligence, and patient engagement.
• AI Infrastructure: Contribute to the design of Generative AI solutions leveraging cloud platforms (AWS, Azure, GCP) or on-premises infrastructure, 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 Generative AI solutions comply with regulatory standards (FDA, EMA, GDPR, HIPAA, GxP, 21 CFR Part 11) and adhere to responsible AI principles, including bias mitigation.
• Performance Optimization: Drive efficiency in generative AI models, focusing on cost optimization and scalability while maintaining data integrity and compliance.
• Stakeholder Collaboration: Work with cross-functional teams, including platform teams and engineering teams from various suppliers/vendors, to align Generative AI initiatives with enterprise and industry-specific requirements.
• Research & Innovation: Stay current with the latest advancements in Generative AI, multimodal AI, AI agents, and synthetic data generation to incorporate emerging technologies.

• bachelors or masters degree in computer science, AI, Data Science, Bioinformatics, or a related field.
• Experience: 8+ years experience in Big data, AI/ML development with at least 6 years in an AI/ML 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).
• Experience in the deployment of a Lightweight LLM in a Pharma SaaS Platform

• MLOps & 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 Generative AI in pharma.
• Problem-Solving: Strong analytical and problem-solving skills with the ability to develop innovative Generative AI solutions for life sciences use cases.
• Communication: Good communication skills to articulate AI solutions to technical and non-technical stakeholders