About the role:

The ML Interfaces Team plays a key role in CoreWeave’s customer journey as the team responsible for supporting and innovating the interfaces our customers use to schedule and drive their machine learning workloads. Initially supporting our Slurm and Knative interfaces, this team has a mandate to keep their fingers on the pulse of the Machine Learning community and provide commoditized solutions targeted to their needs that reduce friction and increase the efficiency and reliability of consuming CoreWeave’s world-class GPU cloud.

We are seeking an engineering leader for the ML Interfaces Team and help us build this specialization from the ground-up. This individual will grow and guide a new team of 4-6 engineers from the early steps of team cohesion and discovery into a high performing group of servant-leaders. As the Manager of this team you would have the opportunity to:

• Drive the culture and tone for how your team keeps score both in how they support each other and how they enable the rest of CoreWeave.
• Support your people and create opportunities for them to be challenged and grow.
• Work directly with other engineering teams to assess needs and guide their implementations and integrations with your team’s platforms.
• Develop processes and standards to achieve a highly mature practice of platform delivery which could serve as a model for other teams at CoreWeave.

Wondering if you’re a good fit? We believe in investing in our people, and value candidates who can bring their own diversified experiences to our teams – even if you aren't a 100% skill or experience match. Here are some qualities we’ve found compatible with our team. If a portion of this resonates with you, we’d love to talk.

• You have six or more years of experience in a software or infrastructure engineering industry
• You love helping people on their journeys to become their best selves.
• You have experience with building and/or leading teams of diverse individuals.
• You believe in a bottoms-up style of leadership that focuses on enablement, communication, organization, and inspiration over task management.
• You have some experience in delivering and/or consuming the domains of scheduler development, ML infrastructure, Kubernetes orchestration, and/or stateful distributed systems.
• You have some prior experience as an engineer with operational responsibilities and can guide the development of a program for reliability, scalability, and observability of ML Interfaces solutions.
• You have some prior experience with Kubernetes and especially the operator pattern for stateful services.