AI platform automating documentation for life sciences companies
Collate builds an AI platform that automates and streamlines paperwork and documentation for drug development, medical device, and diagnostic companies throughout the product lifecycle. It serves life sciences firms to accelerate innovations from concept to market. This reduces manual effort on regulatory compliance, allowing focus on advancing human health.
Product Designer responsible for defining the visual and interaction language for Collate's novel AI document generation platform in life sciences. Work hands-on with founders, engineers, and product to turn complex regulatory workflows into simple, trustworthy interfaces.
Own full-cycle recruiting for GTM teams (Sales, CS, Implementation, Support) at an AI life sciences startup. Build sourcing strategy and pipeline from scratch, evaluate sales talent for regulated industries, and deliver data-driven hiring in a high-ambiguity environment.
Product Manager to define and drive AI product strategy and roadmap for a life sciences document generation platform. Work hands-on with engineering, design, founders, and regulated customers (regulatory/clinical teams) to ship 0-to-1 features in a fast-moving early-stage environment.
Leads end-to-end deployments of AI systems for life sciences customers, embedding with teams to identify issues, build production agents/workflows integrating with their infrastructure, and turn wins into platform patterns. Requires hands-on AI experience, 0-to-1 building, and clear communication across technical/non-technical audiences.
Leads full-cycle implementations of Windchill for life sciences customers, managing onboarding, configuration, and adoption in regulated environments. Requires 8+ years client-facing experience including 2+ years with Windchill and QMS knowledge.
Owns infrastructure for AI document platform in life sciences, building CI/CD pipelines, managing cloud systems (AWS, Kubernetes), monitoring, and light security to ensure reliability and scale.
AI Research Scientist explores novel LLM modeling, NLP, and reasoning approaches for healthcare applications, prototypes capabilities, and deploys them into production with engineering and product teams. Requires strong ML/NLP background with publications and hands-on deep learning experience.
Leads full-cycle enterprise implementations for AI document platform in life sciences, managing customer onboarding, configurations, and adoption while collaborating cross-functionally. Requires 4+ years client-facing experience in regulated industries like biotech.
Build and scale backend services, APIs, and data pipelines using Go, Postgres, and AWS for an AI platform accelerating life sciences innovation. Collaborate with product and ML teams to deliver reliable, performant systems in a fast-paced startup.
Build responsive, performant frontend applications using React and TypeScript to make complex AI-driven healthcare data accessible and intuitive for doctors, patients, and researchers. Collaborate with design, product, and backend teams to own testing, releases, and user experiences emphasizing accessibility and performance.
Build backend-heavy full-stack systems, APIs, data pipelines, and end-to-end features using Go, TypeScript/React, and AWS/Kubernetes. Collaborate with product/design/AI teams, own production systems including on-call, with emphasis on scalability and user experience.
Builds and productionizes AI models and systems for life sciences document generation, focusing on LLMs, NLP robustness, and reliable deployment pipelines. Bridges ML research, software engineering, and product needs in a high-stakes domain.