岗位大厅/Engineering/Inference Performance & Deployment - Member of Technical Staff

Callosum · 178天前 · 来源 雇主官网

Inference Performance & Deployment - Member of Technical Staff

London现场办公
全职Engineering
薪资未披露
Seed 种子
团队 16–16 人
签证支持雇主持牌 · UK(Home Office 名册);岗位明示提供担保(JD 原文)
🇬🇧 永居新规薪资未披露——面试必问。签证线 £41,700;永居快线 £50,270×3 年≈5 年永居

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信号由后台自动核验生成,仅供参考;判断权在你。设计案:GHOST-JOB-P1

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必备技能

AICloudGPUNetworkingNode.jsTriton

免费注册后解锁"你的匹配分 vs 高分画像"与个人技能缺口。

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职位描述

About Us

We’re living through a Cambrian explosion of intelligence: new models and new chips, each specialised for different tasks, are arriving all at once. The result is a new era for AI, one of radical heterogeneity.

Callosum is the Intelligent Systems Company. We believe the next generation of AI won't be defined by any single model or chip, but by intelligent systems in which hardware and intelligence co-evolve. We are building the infrastructure that unifies heterogeneous compute across the full stack. This opens a new axis of scaling intelligence: a dynamic system that tailors itself to what each workload actually needs, whether that's speed, cost, precision, or whatever unit comes next.

The last era scaled on a different bet: one bigger model, more of the same chip, more data. That bet is running into structural limits. Frontier models offer extraordinary capability at unsustainable cost, one that today's monolithic infrastructure was never designed to serve.

Our founding principle is that intelligence comes from many specialised systems working together, not from any single component. We build the software orchestration layer that co-evolves models, workflows and silicon into one system, delivering inference tailored to every workload, and demonstrating orders-of-magnitude leaps in capability and cost.

Because our software spans the full stack, our engineering team works directly with heterogeneous accelerators and frontier silicon, including Cerebras, d-Matrix, Intel, NVIDIA, AMD, Normal Computing, Tenstorrent, GreatSky, and Mixx. We are not stopping at today's chips: each new generation of silicon unlocks algorithms that couldn't run before, and we intend to be first to them, every time. If we get it right, it will belong to everyone building on it - not to any single vendor.

In our latest funding round, we raised $100M, led by Atomico with participation from Plural, DCVC and the UK Sovereign AI Fund’s first investment. With this, we are building the infrastructure for the next era of intelligence.

We are engineers and scientists based in London, working across the full depth of the stack. We are curious, intellectually honest, and building what doesn't exist yet. If you thrive on uncharted territory and are energised by the scale of the challenge, we'd love to hear from you.

About the Role

Callosum believes that orders of magnitude improvements in AI systems will come through application-aware orchestration across heterogeneous hardware. We are building that vision: infrastructure that treats the full landscape of compute as a unified, co-evolving system, evolved beyond GPUs.

This role owns the bridge between Callosum's internal engineering and the real world. You design the tooling and methodologies that ground our technology in real-world performance and behaviour, sitting at the integration point of every engineering function. You will be the first to run our heterogeneous infrastructure in production-equivalent conditions, systematically characterising performance, identifying bottlenecks, and driving decisions on production-readiness. Your work ensures that every layer of the stack is guided by empirical evidence rather than assumption.

What You’ll Build

- Run experiments self-hosting models on cloud instances or on-prem across providers and hardware configurations, systematically characterising performance envelopes

- Develop and maintain deployment patterns that are reproducible, measurable, and optimised for latency, throughput, and cost

- Work at the orchestration and routing software that sits above the inference engine - to improve caching, request scheduling, batching, and resource allocation

- Act as the integration point for the other roles: consume new accelerator support, engine features, and infrastructure upgrades – to provide high-quality feedback on bottlenecks, essential capabilities, and guide the stack optimisations

- Build and maintain benchmarking harnesses, regression suites, and performance dashboards that give the team a shared view of system health and progress

What Sets You Apart

- Experience deploying and benchmarking large model inference in production or production-equivalent environments

- Familiarity with multi-node GPU deployments and associated networking/communication stacks

- Strong end-to-end performance characterisation skills: able to isolate whether a bottleneck is in the network, the runtime, the memory subsystem, or the model itself

- Familiarity with serving frameworks like Dynamo, Triton Inference Server, or similar orchestration layers

- Clear communication skills - able to translate performance data into actionable, prioritised feedback for the teams building the underlying systems

- A demonstrable disciplined and systematic approach to deployment: reproducibility, measurement methodology, controlled comparisons, etc

What We Offer

- Competitive Salary, determined by skills and experience

- Equity & Ownership

- Private healthcare

- We offer Visa sponsorship and relocation benefits to hire the best in the world

- We work in person at our London office. You'll have the tools, space and setup to do your best work, and if you have specific needs, just tell us

We're committed to building an inclusive workplace where everyone feels welcome, and believe in equal opportunities for all.

🈯 翻译这份 JD · 红灯 0 / 黄灯 1 / 绿灯 0点开 ▾
可以投——没有红灯,黄灯问题放进面试清单问清即可。
competitive salary → 形容词,不是数字要问的问题:这个岗位的预算范围是多少?
词典只标"常见信号",不对公司下结论——红灯 = 面试里该当面确认的问题。想自己翻别的 JD:JD 翻译器 →
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公司 · Company

Callosum

Callosum is a London-based AI infrastructure company founded in 2025 by Cambridge neuroscientists Danyal Akarca (CEO) and Jascha Achterberg (CTO), who built sof

London团队 16–16 人Seed 种子来源:雇主官网

⚑ 岗位信息收录自公开招聘页(雇主官网),以雇主官网为准