Teams at Lila Sciences

Provides legal counsel to AI research, product, data, safety, and security teams developing frontier scientific AI systems. Advises on training data, copyright, licensing, privacy, model releases, open-source strategy, research collaborations, autonomous experimentation, biosecurity, AI regulation, export controls, infrastructure, and regulatory inquiries. Builds scalable legal frameworks, playbooks, templates, and self-service guidance for a rapidly evolving AI and life sciences organization.

Lead the inference engineering organization and own Lila’s model-serving platform end to end. Define APIs, serving architecture, batching, routing, deployment, reliability practices, and performance objectives for production LLM systems. Partner with ML, research, product, and executive teams to productionize models, establish evaluation and observability systems, and manage latency, throughput, quality, reliability, and cost. Hire, mentor, and retain engineering talent while setting the serving roadmap and technical strategy.

Own the end-to-end enterprise search and retrieval platform for scientific AI workloads. Build RAG over literature, patents, protocols, and experimental records; develop a scientific knowledge graph; and combine graph, vector, and lexical retrieval into cited, traceable answers. Lead ingestion, document extraction, agentic search, retrieval evaluation, tenancy, permissions, and security. Provide architectural leadership across infrastructure, AI/ML, platform engineering, and scientific teams while coding in Python and deploying cloud-native systems.