Description
We're building a system that represents domain knowledge as modular probabilistic models — making analysis rigorous and transparent. Users can connect these models flexibly into larger structures. The system enforces consistency across them, and propagates uncertainty through each step.
Our first applications are in finance and scientific research, with use cases ranging from equity valuation and distress monitoring, to particle physics. We are looking for strong software engineers to build our program synthesis pipeline. You will be able to choose how close to theory or the production system you want to work, and be exposed to cutting edge research in Bayesian statistics, dynamical systems, information theory, category theory, and more.
g. Rust, OCaml, Clojure, C++, or Haskell Profiling and low level performance optimisation Mathematics, Computer Science, or Statistics advanced degree
Responsibilities
Define new features or fixes, based on awareness of overall objectives and challenges Commit to delivering defined features or fixes end-to-end Define implementation strategies Leverage the expertise of other team members effectively Write design documents for more complex problems Write clean and performant code Help other team members to deliver on their goals Required mindset We've found that our successful team members share some key characteristics, and as we've grown our team, these are the qualities we've learned to seek out. We take pride in our strong, collaborative cultur
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