Teams at Invisible Technologies

Design scalable human-data solutions for frontier AI clients, translating ambiguous model-training and evaluation needs into executable programs. Lead discovery, methodology, task and workflow design, feasibility estimates, expert profiling, quality strategies, and technical architecture in partnership with engineering and project teams. Advise on fine-tuning, RLHF, benchmarks, red teaming, multimodal data, coding tasks, and agent environments while guiding pilots through early delivery and developing reusable best practices.

Build and deploy AI-powered solutions for clients by scoping ambiguous problems, designing LLM workflows, integrating data and retrieval systems, and creating scalable production tooling. Collaborate with technical and non-technical stakeholders, iterate based on operator feedback, optimize workflows, and support customer deployments. The role requires strong Python and software or ML engineering skills, production deployment experience, communication abilities, customer on-call availability, travel as needed, and hybrid office attendance.

Build and deploy AI-powered solutions directly with clients and internal delivery teams. Responsibilities include scoping ambiguous problems, designing LLM and retrieval workflows, developing scalable backend and infrastructure systems, optimizing operational workflows, translating messy data into technical architectures, iterating with stakeholders, and creating reusable deployment tooling. The role also involves client communication, end-to-end project ownership, customer on-call support, travel for client engagements, and hybrid office work.