- Location
- London
- Level
- Mid level
- Posted
- 5 weeks ago
About this role
Silicon Infrastructure Engineer
About Fractile
Fractile was founded in 2022 on the bet that, eventually, the world’s most capable AI systems would be limited in their impact by the time taken to produce useful outputs. We bet everything on the logical conclusion: that the only way to truly unlock this latent value, to make speed viable at scale, was to radically re-invent the hardware that we run our frontier AI models on. Ever since, we have been building chips and systems that tackle this problem: how to efficiently generate output at thousands of tokens per second, while handling the complexity and capacity challenges of operating large models at very long contexts.
The workloads that push to the limits of the current frontier are already transformational; it is the technical and economic limits on inference speed that are constraining progress. The defining work of the 21st century will be marked by the engine of inference delivering immense and diffuse chains of intellectual inquiry, in drug discovery, in software engineering, in materials discovery, in any field where progress is driven by deep reasoning and intelligence to resolve complex problems.
Key Responsibilities:
- Create and support Python tooling and silicon verification and physical design workflows centred around silicon EDA tooling, which will require coding and build-system knowledge to assist with tasks faced by different teams.
- Bazel build system support for new silicon EDA tools required for throughout the chip lifecycle
- Create and improve Python developer tools across frontend and backend silicon teams
- Improve existing workflows to make them cacheable and reproducible
- Work with the engineering team to build and optimise their workloads
It would be great if you have:
- Experience of silicon EDA tooling
- Experience working with build systems tooling, such as Bazel.
- Experience working with workload management tools, such as Slurm.
- Experience working with container orchestration tools, such as Docker, and Kubernetes.
- Experience working with infrastructure as code, such as Ansible, or Terraform and maintaining compute infrastructure
- Experience of setup and monitor observation tooling for resource utilisation, machine failures, and more (e.g. Prometheus/Zabbix)
Preferred Qualifications:
- Proficient in modern software development language(s) especially Python
- Proficient dealing with modern build systems e.g. Bazel, Pants
- Past experience with diagnosing and resolving network/storage/CPU/RAM bottlenecks across complex workloads.
- Experience deploying and managing a grid compute system (Slurm/LSF/SGE).
- Proficiency with containerisation frameworks (Docker/Singularity)
What We Offer
- Competitive salary: A competitive salary reflective of your experience and the specialist nature of the role.
- Equity & Ownership: meaningful equity so everyone shares in the value creation.
- Benefits: Private Medical, Dental and Vision, Contributory Pension, 25 Days holiday plus bank holidays and Life/Critical Illness Insurance.
- Diverse & fun office: we believe the hardest problems get solved by the broadest range of minds. We are committed to Equal Employment Opportunity through attracting and retaining a diverse team and building an inclusive environment.
Fractile is seeking to increase the clock speed of global progress, one chip at a time. We’ve recently raised $220M from investors including Founders Fund and Accel and our most important work lies ahead. Join us!
Export controls
Our work involves technologies subject to UK, US and other international export control regulations. Certain roles may require additional eligibility checks to ensure compliance with applicable law. We'll be transparent about this throughout the hiring process.
As published by Fractile. Applications are handled on their site.
Skills this posting mentions
About Fractile
Fractile is building chips, systems and software to radically improve the speed and cost of running frontier AI inference. Existing hardware is good for training frontier AI models, but very poorly suited to subsequent inference of the trained model, which is increasingly defining the new era of AI compute workloads. Fractile’s revolutionary approach to fusing computation with memory eliminates this bottleneck, and can scale to allow running the world’s largest models at a global scale. We've rearchitected the inference stack from the ground up - silicon to software - to enable generational leaps in capability on the world’s hardest and most important problems.
All 37 openings at FractileOne click, then it is written
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Drop a resume or a LinkedIn URL. I rank the live openings against it, rewrite the resume and write a cover letter for the best of them, and fill in the employer's form when you press the button. You read, you decide what goes out.
01Drop your resume
A PDF or a LinkedIn URL. About a minute, once.
02I rank the openings
Every weekday morning, the live catalog scored against your history. Up to 20 worth your time, not two hundred links.
03Each one is written up
Resume rewritten for the posting, a cover letter, a fit score. Press send, or let me fill in the form.
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