2 months ago
London, United KingdomSenior
Responsibilities
- Develop the core program evolution loop for generating, evaluating, selecting, and evolving candidates over long optimisation runs.
- Design search strategies that balance exploration, exploitation, diversity, and sample efficiency across irregular optimisation spaces.
- Build continuous benchmarks to measure optimiser performance across internal workloads and standalone problems.
- Improve the optimiser through empirical measurement and make regressions visible.
- Turn the optimisation system into reliable, reusable internal infrastructure for new verifiable domains.
Requirements
- Strong foundations in optimisation and search, including evolutionary, stochastic, combinatorial, or other non-gradient-based methods.
- Ability to reason about exploration versus exploitation, diversity, pruning, objective design, and the suitability of different optimisation strategies.
- Strong engineering instincts and experience turning experimental systems into reusable, measurable, and reliable software.
- Demonstrated ability to draw on techniques across optimisation, algorithms, and machine learning rather than relying on LLMs for every problem.
Benefits
- Competitive salary determined by skills and experience.
- Equity and ownership.
- Private healthcare.
- Visa sponsorship and relocation benefits.
- In-person work at the company’s London office with provided tools, workspace, and setup.
Categories
AI Research
About Callosum
Callosum builds AI infrastructure that unifies heterogeneous compute—software and systems to orchestrate diverse accelerators and the physical clusters they run on—for organizations training and serving models. The privately held company was founded in 2025 and is headquartered in London. It focuses on designing, deploying, and operating mixed-hardware compute fleets across sites and vendors, and raised a seed round in 2026.