Hardware-Aware Model Optimisation
Callosum
Hardware-Aware Model Optimisation
Callosum
Orchestrates AI workloads across specialized silicon
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.
Callosum believes that the next generation of AI systems will emerge from models and hardware being optimised together. Today's model architectures have largely evolved around the capabilities of conventional GPUs, leaving significant opportunities unexplored as new accelerator architectures emerge. We are building infrastructure that allows models to be adapted to different computational substrates, rather than treating them as fixed algorithms that hardware must accommodate.
This role explores how model architectures and inference algorithms can be adapted to exploit heterogeneous hardware, creating specialised variants with different trade-offs between capability, latency, and cost. You will investigate transformations spanning numerics, sparsity, model structure, memory, and execution, alongside new algorithms designed around emerging accelerators. A central part of the work is developing automated approaches to these adaptations and rigorous evaluations that establish when the resulting models offer meaningful advantages.
Develop hardware-aware transformations that adapt models to different accelerator architectures and execution environments.
Explore numerical, structural, and memory-related optimisations to create model variants with different capability, latency, and cost trade-offs.
Investigate new inference algorithms, including speculative decoding, designed to exploit heterogeneous computational resources.
Develop automated methods for discovering, characterising, and optimising hardware-specialised model variants.
Build evaluation methods that measure model quality and establish the trade-offs introduced by hardware-aware adaptations.
Deep understanding of modern LLM architectures, including attention mechanisms, model structure, and their implications for inference.
Experience in model architecture research, efficient inference, or hardware-aware machine learning.
Familiarity with a range of architectures, such as mixture-of-experts, diffusion, JEPA, or alternative attention mechanisms.
Strong intuition for the interactions between model capability, numerical behaviour, memory requirements, and execution efficiency.
Experience designing rigorous experiments to assess model quality, efficiency, and the effects of architectural modifications.
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.
Callosum builds AI infrastructure that unifies different AI models and hardware chips to run workloads on the best combination of model and chip for each task. Its Tailored Inference APIs route tasks to the optimal model–chip pair while honoring cost, energy, and latency constraints, using partners like Cerebras and Rebellions for specialized silicon. Unlike approaches that rely on one model and uniform hardware, Callosum orchestrates multiple models and chips to maximize efficiency. The company's goal is to enable scalable, cost-efficient AI inference across heterogeneous hardware by intelligently matching tasks to the right combination of model and accelerator.
Explore more opportunities at Callosum