• Design and build Machine Learning platform components that support agentic systems, including retrieval pipelines, indexing strategies, and model integration layers. • Introduce and operationalize RAG use cases, from data sourcing and embedding generation to runtime retrieval patterns. • Develop generalized evaluation frameworks for LLM- and agent-based features, including offline metrics, golden datasets, and continuous monitoring. • Implement abstractions, tooling, and reusable patterns that enable other teams to build ML- and LLM-powered experiences efficiently. • Partner with backend engineers to productionize ML features with strong reliability, observability, and performance characteristics. • Prototype applied ML solutions to validate feasibility before investing in full builds. • Ensure secure, robust handling of data used in ML workflows and retrieval operations. • Collaborate with product, design, and engineering to align ML system design with user experience and product goals. • Contribute to iterative improvements of the Nova agent framework, including workflows built with Mastra and TypeScript.

• Design, maintain, automate, and optimize ML training pipelines and realtime model serving infrastructure • Improve ML observability, model evaluations, model monitoring, and debugging tools • Collaborate closely with ML scientists and engineering teams • Develop new ML solutions to extract information from studio artifacts • Stay updated with ML infrastructure advancements and new technologies

• Lead the development and integration of cutting-edge artificial intelligence and machine learning (AI/ML) solutions into our imaging platform for clinical trials. • Shape and execute an ambitious AI/ML strategy aligned with our R&D roadmap. • Define technical architecture, establish best practices, and champion AI/ML capabilities across the organization. • Manage talent, foster innovation, and cultivate a culture of technical excellence and collaboration. • Serve as a key thought partner to senior leadership, providing updates on AI/ML initiatives, progress, risks, and opportunities.

• Participate in agile development processes, including sprint planning and daily stand-ups • Collaborate with cross-functional teams (data scientists, software engineers, product managers, business leads) to define requirements and deliver high-quality ML solutions. • Develop and implement end-to-end AI/ML models and workflows within the Palantir Foundry and AIP environment • Leverage Palantir AIP features, such as Agent Studio, RAG (retrieval-augmented generation) workflows, and copilots, to ground models in relevant data sources and the Ontology. • Conduct research on open-source tools and ML techniques relevant to the medical domain • Design, implement, and optimize advanced machine learning algorithms to solve complex business problems. • Lead the development and deployment of scalable and efficient ML models in production environments. • Drive research and experimentation to explore new ML techniques, tools, and frameworks. • Build end-to-end data pipelines for collecting, processing, and analyzing large-scale datasets. • Mentor junior engineers and contribute to the development of team processes and best practices. • Stay up-to-date with the latest trends and advancements in machine learning and AI.