SUMMARY: The AI / ML Engineer will design, develop, and scale AI-powered data products to enhance Worldwide's services and improve the efficiency of clinical research processes. This role focuses on the end-to-end lifecycle of data products, utilizing the Databricks platform and a variety of advanced LLM tools to create innovative solutions that drive business value.
RESPONSIBILITIES:
Tasks may include but are not limited to:
• Collaborate with cross-functional teams to identify business needs and translate them into production-ready data products.
• Develop, test, and deploy AI models and data pipelines within the Databricks environment using Python and SQL.
• Manage the full machine learning lifecycle using Databricks MLOps tools to ensure model versioning, tracking, and seamless deployment.
• Leverage Databricks AI and ML offerings, including Genie and Genie Code, to provide natural language interfaces for data exploration.
• Build and maintain autonomous agents and workflows using Agentbricks and related frameworks.
• Implement and fine-tune solutions using a diverse set of LLMs, including Claude, Gemini, and ChatGPT, to solve complex business problems.
• Utilize developer productivity tools such as Claude Code to accelerate the delivery of AI solutions.
• Optimize and improve the performance of existing prompts and agentic workflows through advanced prompt engineering.
• Stay up-to-date with the latest developments in AI, LLM ecosystems, and Databricks features to identify new opportunities for application.
• Translate technical concepts and findings into clear language for non-technical stakeholders.
• Provide training and support to end-users on AI-related tools and data products.
•Create comprehensive documentation for AI models, code, and MLOps processes to facilitate knowledge sharing and troubleshooting.
• Design AI solutions with scalability and security in mind, ensuring they can handle increasing clinical data volumes.
• Investigate and resolve issues related to AI model performance, data drift, or system functionality.
• Ensure compliance with relevant AI-related regulations and data privacy standards within the clinical trials industry.
• Perform other duties as assigned. The duties and responsibilities listed above are representative of the nature and level of work assigned and are not necessarily all inclusive.