Head of Engineering (Hybrid)

Job Description Our client Cleanlab is focused on data-centric AI (DCAI), providing algorithms/interfaces to help companies (across all industries) improve the quality of their datasets and diagnose/fix various issues in them. They develop next-generation DCAI algorithms that they release publicly as open-source software (github.com/cleanlab/cleanlab) as well as enterprise SaaS products with interfaces for data scientists/engineers to effectively improve their data quality and produce more reliable ML models. We're looking for someone whose love for people and AI/technology runs incredibly deep, as does their ambition to improve the way Data Science and Machine Learning are practiced in the future. You should currently work as an engineering manager but have extensive software engineering experience, ideally with experience in a dynamic startup environment. You should be comfortable architecting large-scale software systems from the ground up, and deeply familiar with MLOps and modern cloud applications. You will manage a team of software engineers building a cutting-edge cloud application with many users, who each have many datasets, some of which are quite large. Your contributions to our client's SaaS tool will be used by data scientists/engineers across all industries to improve the quality of their data and reliability of ML models produced from this data. Come help us build the next generation of data-centric AI • Build and run one of the strongest engineering teams in existence, pioneering novel data-centric AI software. Our tools enable data scientists/engineers (across all industries) to effectively diagnose/fix issues in their datasets thus improving the quality of their business's core asset. • Work with great people on interesting challenges (model deployment/monitoring, managing massive datasets, rapidly scaling cloud deployments, etc.) at a dynamic startup operating in one of the fastest growing subfields of data science & AI. • You will manage a team of software engineers building a cutting-edge cloud application with many users, who each have many datasets, some of which are quite large. Your contributions to our SaaS tool will be used by data scientists/engineers across all industries to improve the quality of their data and reliability of ML models produced from this data. Requirements • Deeply familiar with MLOps and modern cloud applications. • Be comfortable architecting large-scale software systems from the ground up • People-oriented and experience running software development teams • Be up to date on modern tech stack for cloud applications • Be up to date on the modern MLOps and Data stack • Ideally has experience in a dynamic startup environment. • At least 7 years work experience spanning software engineering/architecture and team management • Currently work as an engineering manager but have extensive software engineering experience • Comfortable architecting large-scale software systems from the ground up • Love for people and AI/technology runs incredibly deep • Has ambition to improve the way Data Science and Machine Learning are practiced in the future. • Experience in a dynamic startup environment