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.