Distributed Systems Engineer

Role overview Build the core systems behind a durable runtime for data processing and machine learning applications. You’ll design and implement infrastructure that other engineers use to run workloads, with responsibility spanning scheduling, execution, performance, and product delivery.

Responsibilities - Evolve the runtime to support advanced data and machine learning workflows. - Design scheduler components that improve cluster resource use, cost, and performance. - Build data plane and execution engine components in Rust or another systems language. - Develop new capabilities for software development kits. - Take engineering ideas from early exploration through implementation and polished product delivery.

Requirements - At least five years designing and building distributed systems infrastructure. - Production experience with Rust or another systems programming language, such as C, C++, or systems-level Go. - Implementation-level understanding of schedulers, databases, or runtimes, gained by building or contributing to them. - Ability to independently design and deliver fault-tolerant systems. - Interest in low-level performance work involving areas such as memory allocation, concurrency, and network protocols. - Willingness to contribute across product development, from customer research to implementation.

Benefits and work setup The team works remotely across the US and Europe, with a high degree of individual ownership and an emphasis on following through on commitments. The role primarily uses Rust, Python, and FoundationDB, with some work involving TypeScript, Go, and Terraform.