• Develop the long term vision and roadmap for Artera’s AI platform that will allow the company to continue to scale in terms of both increased inference volume and development workloads. • Accountable for Artera’s ML compute infrastructure including scaling up Artera’s Foundation Model development by developing distributed training infrastructure and developer libraries. • Build and evolve the core libraries used by AI scientists to develop, launch, and monitor AI products. • Work with model developers to optimize GPU and CPU efficiency and data throughput of large-scale foundation models and downstream model training runs. • Optimize Artera’s ability to store and serve terabytes of digital pathology data efficiently for the use in serving large-scale training regimes. • Ensure that Artera’s observability infrastructure provides a clear picture of how to continue to optimize performance across our model landscape.