Senior Director, Machine Learning

We are looking for a Senior Director of Machine Learning to lead and scale our computer vision and ML efforts, with teams based in India and Europe. This role goes beyond individual contribution - you will be responsible for defining the long-term ML vision, building and leading high-performing global teams, and driving the development of production-grade systems that power item authentication and fingerprinting at scale. You will own the end-to-end ML strategy from research and algorithm development to deployment, infrastructure, and continuous improvement, ensuring alignment with business goals and customer impact. This is a highly cross-functional leadership role requiring deep technical expertise, strong organizational leadership, and the ability to operate effectively across geographies. As a senior leader, you will shape the future of our ML capabilities, strengthen India as a core hub, and drive collaboration across distributed teams. Reports to: CTO Location: Bangalore, India (Hybrid)

: • Lead & Scale the Organization: Build, lead, and evolve a high-performing, globally distributed ML team across India and Europe. Define team structure, hire and develop senior talent, establish clear ownership, and create a culture of accountability, rigor, and high-quality execution. • Define Strategy: Own the ML and computer vision roadmap, aligning technical direction with business priorities and customer impact. Translate company goals into a clear, executable plan with measurable outcomes. • Drive Execution: Ensure consistent delivery of production-grade ML systems from research to deployment — with a focus on scalability, reliability, and speed. Balance long-term innovation with near-term impact. • Advance Core Capabilities: Guide the development of computer vision models for authentication and fingerprinting, ensuring models are accurate, robust, and practical for real-world use. • Build Systems & Infrastructure: Oversee ML infrastructure, training and inference pipelines, and deployment systems. Drive optimization for performance, including edge deployment, latency, and efficiency. • Cross-Functional & Global Collaboration: Partner closely with product, engineering, and operations teams to define priorities and deliver outcomes. Drive alignment and effective execution across India and Europe teams, ensuring clarity, consistency, and strong communication across geographies. • Ensure Operational Rigor: Establish best practices, define success metrics, and drive continuous improvement across models, systems, and team processes. Use data and production feedback to inform decisions and improvements.