Systems Software Engineer
- Hiring from
- United Kingdom
- Work type
- Hybrid
- Posted
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About The Company
CommonAI CIC is a non-profit organisation focused on collaborative engineering, supported by a combination of UK Government and private funding. Our mission is to design, build, and deploy innovative artificial intelligence systems that advance the state of AI infrastructure. Within CommonAI, the Scaling Inference Lab (SIL) develops simulation tools grounded in real-world measurements, enabling the UK to make informed investments in promising AI infrastructure. By linking proposed hardware designs with realistic workloads, SIL helps investors and engineers understand the potential and limitations of new technologies, guiding the next steps in experimentation and development.
About The Role
We are seeking a skilled software engineer to develop software that enables SIL to configure and control real AI infrastructure for reproducible experiments. This role involves transforming the capabilities of experimental clusters into programmatic controls that manage workload placement, resource allocation, and inference-serving configurations. The core engineering challenge is to ensure these changes are dependable by accurately understanding the current system state, verifying the feasibility of actions, confirming outcomes, and managing failures.
You will collaborate closely with measurement and simulation engineers as well as cluster operators to establish robust controls for initial experimental studies. The interfaces you develop will also serve as the foundation for future design-space optimisation software. An early project example includes building an interface for changing serving configurations and demonstrating repeatable experiments across different configurations, including verification and recovery mechanisms.
Qualifications
CommonAI CIC is a non-profit organisation focused on collaborative engineering, supported by a combination of UK Government and private funding. Our mission is to design, build, and deploy innovative artificial intelligence systems that advance the state of AI infrastructure. Within CommonAI, the Scaling Inference Lab (SIL) develops simulation tools grounded in real-world measurements, enabling the UK to make informed investments in promising AI infrastructure. By linking proposed hardware designs with realistic workloads, SIL helps investors and engineers understand the potential and limitations of new technologies, guiding the next steps in experimentation and development.
About The Role
We are seeking a skilled software engineer to develop software that enables SIL to configure and control real AI infrastructure for reproducible experiments. This role involves transforming the capabilities of experimental clusters into programmatic controls that manage workload placement, resource allocation, and inference-serving configurations. The core engineering challenge is to ensure these changes are dependable by accurately understanding the current system state, verifying the feasibility of actions, confirming outcomes, and managing failures.
You will collaborate closely with measurement and simulation engineers as well as cluster operators to establish robust controls for initial experimental studies. The interfaces you develop will also serve as the foundation for future design-space optimisation software. An early project example includes building an interface for changing serving configurations and demonstrating repeatable experiments across different configurations, including verification and recovery mechanisms.
Qualifications
- Experience building systems software or automation tools that configure and control real computing infrastructure.
- Strong programming and debugging skills, with practical knowledge of Linux and associated hardware/software interfaces.
- Expertise in one or more of the following areas: cluster or HPC automation, distributed systems, orchestration, device control, networking, or experiment-control software.
- Ability to reason about partial failure, system state, permissions, and the impact of changes on running systems.
- Practical experience using AI coding agents, with sound judgement to validate generated code and safely test changes affecting hardware or infrastructure.
- Familiarity with accelerators, job-control systems, Kubernetes, Slurm, operating systems such as NixOS or CoreOS, or Infrastructure as Code (IaC) tools like Terraform or OpenTofu is advantageous but not mandatory.
- Relevant postgraduate study is beneficial but not essential; emphasis is placed on experience and quality of work.
Responsibilities
CommonAI CIC is an equal opportunity employer committed to fostering an inclusive and diverse workplace. We welcome applications from all qualified individuals regardless of race, gender, disability, age, sexual orientation, religion, or any other protected characteristic. Our hiring practices emphasize fairness and respect for all candidates, creating an environment where everyone can thrive and contribute their best work.
- Identify and expose controls available on selected clusters through documented, programmatic interfaces with clearly defined supported actions.
- Automate configuration and experiment setup across the technology stack, including workload placement, serving settings, resource allocation, and device configuration.
- Develop reliable execution workflows incorporating precondition checks, outcome verification, error handling, and recovery to known configurations.
- Record all requested actions, outcomes, and resulting configurations to enable reproducibility and accurate interpretation of experimental results.
- Coordinate access, permissions, and configuration changes with cluster operators, and rigorously test success, failure, and recovery scenarios within agreed experimental scopes.
- Design interfaces that can be leveraged by future optimisation software, with explicit capability limits and clear outcomes when actions cannot be completed.
- Collaborate with cross-functional teams to ensure software meets the needs of experimental studies and infrastructure management.
- Opportunity to contribute to the advancement of UK AI capability and influence how compute resources serve the public good.
- Engagement with a broad network including UK hardware SMEs, major technology companies, venture and public investors, and leading academic institutions.
- Participation in shaping a dynamic team that combines startup agility with strong academic connections.
- Access to cutting-edge AI models and coding agents supported by a substantial tooling budget.
- A collaborative and supportive work environment that values impact and innovation.
- Competitive salary package with pension and benefits.
- Professional development and networking opportunities with influential figures across the technology and academic sectors.
- Vibrant office location within walking distance of Cambridge train station.
- Flexible hybrid working arrangements with options for permanent, part-time, or consultancy roles.
CommonAI CIC is an equal opportunity employer committed to fostering an inclusive and diverse workplace. We welcome applications from all qualified individuals regardless of race, gender, disability, age, sexual orientation, religion, or any other protected characteristic. Our hiring practices emphasize fairness and respect for all candidates, creating an environment where everyone can thrive and contribute their best work.
