Savernake Capital is a quantitative investment management company specialising in adaptive machine learning.
We utilise an asset class agnostic self-learning strategy and portfolio-building system, designed over the past 10 years, to trade global financial markets; adapting in real-time to changing market conditions and patterns. This approach enables us to produce exceptional returns for our investors whilst protecting against strategy decay.
We are an engineering-led firm focused on building long-lived, production-grade systems that operate under uncertainty.
Our work sits at the intersection of systems engineering, mathematics, and applied research. We care deeply about how complex systems behave over time - not just how they perform in ideal conditions.
We are deliberately small, highly technical, and long-term in our thinking. Everything we build is designed to survive, adapt, and improve over multiple generations.
Our approach
We care less about individual ideas and more about systems that behave well over long periods of time.
Accordingly, our decisions are guided by constraints rather than targets. We prioritise:
Robustness over peak performance
Consistency over occasional brilliance
Survivability over theoretical optimality
Our engineers understand that many of the hardest problems only emerge after systems have been running for years. It’s why our systems are designed to be observable, debuggable, and stable in production. We favour explicit data flows, deterministic behaviour, simple components, and clear failure modes.
Working at Savernake
Savernake is grounded in production reality, system health, and long-term robustness. As such, we want our engineers to be intellectually honest, boasting strong fundamentals, curiosity, and a long-term mindset.
We are looking for driven, ambitious individuals to join us on our mission to create an ever-evolving quantitative system that produces exceptional returns.
Please see our current vacancies listed below, and click here for our recommended reading list that all prospective candidates would be wise to consult before applying to join the team.
