Teams at Invisible Technologies

Build and deploy end-to-end statistical and machine learning solutions for clients and internal delivery teams. Responsibilities include scoping ambiguous problems, analyzing operational challenges, prototyping AI workflows, translating messy data and real-world constraints into scalable solutions, iterating with stakeholders, and developing reusable tooling and infrastructure. The role combines hands-on data science with technical consulting and requires communication with technical and non-technical stakeholders.

Lead end-to-end data science and machine learning projects, from scoping ambiguous client problems through production deployment. Build and evaluate statistical and ML models, analyze large datasets, run experiments, collaborate with engineers, create reusable tooling, communicate findings to diverse stakeholders, and mentor data scientists. The role combines hands-on data science with technical consulting and requires occasional customer on-call support.

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.