Jobber Benefits Overview

Owns production machine learning systems and automated decisioning, including graph-based models, RAG systems, real-time serving, monitoring, evaluation, drift detection, and retraining. The role establishes ML engineering and MLOps standards, shapes platform strategy, mentors scientists, and partners with senior leaders. Responsibilities include developing SignalGraph, improving LLM evaluation, applying modern deep learning methods, and communicating technical decisions and uncertainty to cross-functional stakeholders.

Build and own production AI systems as the founding technical engineer within Jobber’s Office of the CEO. Architect systems end to end, including LLMs, retrieval, agents, integrations, permissions, security, reliability, and quality. Embed with teams to deliver AI into real workflows, evaluate build-versus-buy decisions, run rapid proofs of concept, and establish trustworthy AI standards. The role requires executive communication, pragmatic technology choices, and Staff-plus experience delivering systems used daily at scale.

Build and own production AI systems as Jobber’s founding AI engineer. The role covers end-to-end architecture, retrieval quality, permissions, security, reliability, LLMs, agents, integrations, and workflow deployment. You will partner with teams and executives, evaluate build-versus-buy options, run rapid proofs of concept, establish technical standards, and deliver trustworthy AI systems used across the company.