Paige.AI is a software company leading a digital transformation in pathology by leveraging advanced Artificial Intelligence (AI) technology in its products to enable a cloud-based workflow for pathology. This AI is powered by an agreement with Memorial Sloan Kettering (MSK), a global leader in cancer care, for exclusive access to millions of pathology slides and pathologist reports. We are backed by a $25 million series A financing and are the first to have AIRI, the most advanced architecture ever built for scale-out AI, with a GPU performance of over 10 petaFLOPS.
We’re seeking a VP of Engineering to join us. In this role you’ll be working with world-leading experts in machine learning, computer vision and pathology. You will be responsible for driving architecture, product development and security for the complete system at Paige.AI. You will guide engineers in cross-functional teams, ranging from front end, back end, AI/machine learning, high performance computing, visualization, cloud and infrastructure.
Implement modern agile and DevOps development practices for fast, high quality and iterative product development.
Own the SDLC, from architecture to development, release and maintenance while adhering to regulatory, security and privacy compliance requirements.
Provide hands-on support across all development teams.
Build on our culture of innovation, while advocating engineering best practices through code reviews and strategic guidance.
Communicate effectively at all levels of the organization, including translating technical concepts to non-technical stakeholders and customers
Driving security and internal IT.
5+ years’ experience using high performance software development methodologies and working across the business to develop and deliver products.
2+ years’ experience managing, hiring, organizing and leading teams of skilled engineers.
A bachelor’s degree or higher in computer science or related field.
Outstanding communication, interpersonal, and leadership abilities.
Machine learning, GPU, parallel processing, and large scale distributed HPC and/or cloud computing environments.
Experience working with scientists as well as engineers.
Containerized environments (Docker, Kubernetes).
Experience with regulated software development, FDA, ISO, HIPAA, GDPR.