Index Exchange
Index Exchange builds a supply-side platform for programmatic advertising, helping digital media owners monetize inventory and connect with marketers across screens. The company operates a global ad exchange and related tooling, running primarily on its own infrastructure and processing more than 550 billion real-time auctions per day. Founded in 2003 and privately held, Index Exchange is headquartered in Toronto and serves publishers in major advertising markets worldwide.
Open Positions at Index Exchange
6 open positions
Lead the architecture and development of Index Exchange’s globally distributed Index Cloud platform, building Kubernetes infrastructure, platform APIs, and developer tooling at internet scale. This Staff-level role focuses on creating foundational systems rather than day-to-day operations.
Lead the architecture and delivery of Index Cloud, a globally distributed platform supporting internet-scale real-time advertising workloads. This Staff role builds Kubernetes infrastructure, infrastructure-as-code frameworks, platform APIs, and developer tooling rather than handling day-to-day operations.
Lead database reliability engineering across global data domains, driving technical strategy, operational rigor, and scalable database platforms. This staff-level role combines deep database expertise with reliability leadership across Kubernetes, bare metal, and cloud environments.
Senior Storage Engineer responsible for designing, operating, and optimizing planet-scale Ceph storage infrastructure for a high-volume global advertising platform. The role combines distributed storage, automation, monitoring, disaster recovery, and cloud platform operations in a remote environment.
Lead the architecture and delivery of large-scale machine learning solutions for Index Exchange’s high-volume digital advertising platform. This role focuses on production ML systems, model deployment, data pipelines, and real-time inference at internet scale.
Senior Machine Learning Engineer leading the design and productionization of enterprise-scale MLOps platforms and high-performance machine learning systems. The role combines model lifecycle governance, scalable backend engineering, and low-latency inference at internet scale.