Establish and lead our Data Intelligence team on-site for end-to-end Machine Learning data lifecycle, overseeing Data Curation & Labelling, MLOps Infrastructure, and Data Program Management
Job Summary
Establish and lead our Data Intelligence team on-site for end-to-end Machine Learning data lifecycle, overseeing Data Curation & Labelling, MLOps Infrastructure, and Data Program Management.
Define the roadmap for the company’s Machine Learning data strategy, including build-vs-buy decisions for labelling tools and MLOps infrastructure, while establishing company-wide standards for data privacy, security, and bias mitigation.
Lead and mentor a multidisciplinary team consisting of ML Automation Engineers, MLOps Engineers, and Data Project Managers, partnering with product, engineering, and robotics teams to deliver high-quality data.
Matching Summary
Establish and lead our Data Intelligence team on-site for end-to-end Machine Learning data lifecycle, overseeing Data Curation & Labelling, MLOps Infrastructure, and Data Program Management.
Skills & Requirements
Must-have
Machine Learning data strategy
end-to-end Machine Learning data lifecycle
Data Curation & Labelling
MLOps Infrastructure
Data Program Management
Data supply chain for AI products
company-wide data standards
Nice-to-have
culture of quality, innovation, accountability
process improvement and tangible outcomes
emerging trends and new technologies
clear thinking even under pressure
relentless attention to detail
Key Requirements
10+ years in Data Management, Engineering, or AI Operations
5+ years in a people management role
Experience scaling an ML organization
Architect high-level data flows
Deep understanding of Machine Learning lifecycle
Solid grounding in data sovereignty, encryption, anonymization