Staff Software Engineer (System Orchestration)

Join Oxford Ionics as a Staff Software Engineer in the System Orchestration team. In this hands-on engineering role, you will build and operate the software that keeps our quantum computers calibrated and running efficiently. You will work closely with various teams, including the runtime team, systems teams, operators, and scientists. Your contributions will directly impact the success of our System Software function and the advancement of quantum computing technology.

Contribuer à la construction et à l'exploitation du logiciel qui maintient nos systèmes calibrés, décide de leurs actions et enregistre leurs activités.

Responsibilities

• Collaborer avec les équipes de runtime, de systèmes et d'exploitation pour assurer la livraison efficace d'un système dont dépend chaque machine de la flotte.
• Prendre en charge les problèmes qui traversent l'ensemble du plan de contrôle, en améliorant la durabilité et les contrats de récupération.

Requirements

• To be successful, you will need deep systems engineering experience, a track record of operating services where losing data is not an option, and the judgement to tell a problem worth solving structurally from one worth patching. We're looking for someone who wants to stay hands-on in the code at this level and can contribute effectively within a fast moving, highly technical team
• Deep experience building and operating stateful networked services in production, exposed over gRPC or REST, with a real grasp of error handling, observability and failure modes
• Expert systems engineering skills. Our System Orchestration layer is written in Rust, so either solid Rust experience or deep proficiency in another systems language and the appetite to work in a Rust codebase, including async programming
• A track record of pinning down failures that others could not
• Excellent communication skills both within software and across disciplines
• A track record with data durability and correctness - persistence design, crash recovery, and migrations against live data you cannot afford to lose. We use PostgreSQL
• Depth in the scheduling and workflow landscape - Temporal, Hatchet, Airflow, Slurm, Postgres-backed queues - and the judgement to borrow from it rather than reinvent
• A habit of settling design questions in writing, with the options compared as peers
• The instinct to reach for determinism when chasing a timing or interleaving bug, rather than for more logging