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PlantingSpace · 3 months ago

Bayesian Software Engineering

United States

Full-time

Remote

Mid Level

Plantingspace is building an AI system aimed at enhancing analytical and scientific reasoning. They are seeking Software Engineers with a background in Bayesian statistics to develop models and algorithms for statistical inference and machine learning, focusing on designing and implementing scalable statistical procedures.

Information TechnologySoftware

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, and work with others to implement them

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

Qualification

Bayesian statisticsProbabilistic programmingStatistical modelingMCMC methodsJulia programmingConstrained optimizationFunctional programmingTeam collaborationProblem-solving

Required

Production backend software engineering

Design and implementation of probabilistic programming language features

Implementation of Bayesian inference methods such as MCMC, SMC or VI

Statistical modeling of real-world scenarios

Constrained optimization algorithms

Functional or typed programming

Only language used in the core of our system: Julia

Can help if you don't know Julia: Rust, OCaml, Clojure

Also useful: C++, Haskell

A builder at heart: You're passionate about building things, solving complex problems, and approaching challenges with an entrepreneurial spirit and humility

Results-driven: You thrive when taking full ownership of tasks, seeing them through from start to finish, and taking accountability for the results

Growth mindset: You are intellectually curious, have a critical mind, and seek opportunities to stretch your abilities

A strong collaborator: You naturally communicate with clarity and purpose, ensuring your ideas and updates are easily understood

Approaching problems and tasks like a project manager: You can take a given goal and break it down into smaller parts