We are seeking a Lead ML / AI Engineer to design and lead end-to-end ML/AI systems spanning computer vision, large language models, and retrieval-based architectures. You will build production-grade intelligence that powers products, operations, and newsroom workflows—while creating foundational AI capabilities that scale across the VERSANT portfolio. This role combines hands-on architecture with platform vision. You will guide model selection, experimentation, and integration into applications; establish rigorous standards for deployment and monitoring; and partner with Product, Engineering, Data, Executive Leadership, and Editorial teams to deliver high-impact systems. You will also mentor engineers and maintain a high bar for technical excellence across the ML lifecycle. Responsibilities Set the technical vision for ML/AI at VERSANT, translating business and newsroom priorities into a focused, high-impact execution roadmap. Architect and implement end-to-end ML systems (data → training → evaluation → deployment → monitoring) across vision, language, and retrieval domains, making high-leverage model and systems decisions that balance performance, latency, cost, and long-term maintainability at scale. Lead model evaluation and monitoring strategy: define rigorous offline and online evaluation frameworks, establish performance benchmarks, and implement feedback loops that continuously improve model quality, safety, and real-world impact. Develop deep expertise in the AI vendor landscape (foundation models, tooling, infrastructure providers), rigorously assess strengths, weaknesses, cost structures, and risk profiles, and guide teams in selecting the right solutions for their specific use cases. Identify cross-brand leverage points and develop reusable AI primitives, APIs, and shared services that reduce duplication and scale efficiently across the VERSANT portfolio. Partner directly with Editorial and product leaders to embed AI into newsroom workflows, content intelligence, and audience experiences. Partner closely with software engineering teams to ensure AI-powered applications are delivered with reliability, resiliency, and scalability as first-order requirements. 
