Callosum
Inference System & Performance Engineer - Member of Technical Staff
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About Us
The last era of AI scaled on a single bet: bigger models, more identical chips, more data. As problems grow more complex and the requirements of intelligence more diverse, that bet is breaking down. Real-world problems are heterogeneous: no single model or chip can solve them alone. The next era of AI requires heterogeneity at the infrastructure level - diverse models on diverse chips, each with distinct strengths, co-evolving into systems of capability that move the Pareto frontier of what is possible. That's what we are building.
Callosum is the Intelligent Systems Company. We started from questioning what actually creates intelligence. We believe there is no single answer, but rather a system-level solution. We co-evolve models, workflows, and silicon together to show that intelligence does not come from a single component, but it emerges from the diversity of co-optimised mechanisms working together and aware of each other. Heterogeneity will define the next era of compute, and is a principle that holds in biological, neuronal, and economic systems alike.
In early 2026 we launched with results showing orders of magnitude improvements in performance, and this is only the beginning. Agentic AI is the future of how intelligence is deployed: multi-step, long-horizon, and operating in changing environments. These systems are inherently heterogeneous, and can only be as powerful as the infrastructure that runs them.
We are engineers and scientists based in London, working together 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.
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About The Role
Standard inference architectures typically focus on monolithic chip types and model classes. Callosum intentionally breaks this mold, operating heterogeneous hardware at scale across a diverse model portfolio. Success in this environment requires an inference layer built entirely from first principles.
Sitting at the heart of our technical mission, this position owns end-to-end performance for our inference platforms. Your focus will span KV cache strategies, batching internals, memory management, and multi-node scheduling. You will develop the core software driving execution speed, silicon efficiency, and platform scalability as we expand our hardware and model footprint. This is a high-leverage role tackling complex system challenges across the entire stack.
What You’ll Build
- Design and optimise inference serving systems across heterogeneous multi-GPU and multi-node environments
- Own KV cache lifecycle management, batching strategies, and memory allocation to maximise throughput and minimise latency
- Profile and tune GPU kernels, identify bottlenecks across compute, memory, and network, and implement targeted optimisations
- Build and improve scheduling logic for continuous batching, disaggregated prefill/decode, and speculative decoding
- Work with networking primitives - NCCL, NVLink, RDMA, InfiniBand, RoCE - to optimise communication across distributed inference workloads
- Develop tooling for performance visibility, regression detection, and benchmarking across hardware configurations
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What You Bring
- Deep understanding of LLM inference internals: KV cache lifecycle, memory management, attention mechanisms, and serving architectures
- Strong systems engineering background with proven experience optimising distributed GPU workloads
- Proficiency in C++, CUDA, Python, Rust, or similar - and the instinct to go low-level when it matters
- Hands-on debugging skills across GPU, networking, and Linux systems - able to work from first principles with limited tooling
What Sets You Apart
- Experience building or significantly optimising production-grade, high-throughput model serving stacks
- Multi-GPU and multi-node inference optimisation using NCCL, NVLink, RDMA, InfiniBand, or RoCE
- GPU memory profiling, CUDA or Triton kernel optimisation
- Linux performance analysis and optimisation
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.
Compensation Range: £101K - £192K
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