PlantingSpace
Artificial Intelligence • SaaS • Enterprise
PlantingSpace is developing an advanced AI system that aims to represent knowledge and uncertainty to facilitate the discovery of insights and enable transparent problem-solving. The company is addressing the challenges of accessing and combining vast amounts of information spread across various mediums such as websites, databases, and scientific literature. Their system uses a probabilistic framework for reasoning and learning, making use of components like category theory, Bayesian statistics, and deep learning to improve the transparency and reliability of AI's reasoning capabilities. PlantingSpace's approach involves developing a universal language for representing heterogeneous information and employing a visual and natural language representation to make reasoning processes understandable. The company provides their AI services in various domains, acting as research assistants, analysts, or data scientists, and focuses on harnessing cutting-edge AI techniques to enhance analysis and problem-solving.
Bayesian Software Engineer
Job not on LinkedIn
October 23
PlantingSpace
Artificial Intelligence • SaaS • Enterprise
PlantingSpace is developing an advanced AI system that aims to represent knowledge and uncertainty to facilitate the discovery of insights and enable transparent problem-solving. The company is addressing the challenges of accessing and combining vast amounts of information spread across various mediums such as websites, databases, and scientific literature. Their system uses a probabilistic framework for reasoning and learning, making use of components like category theory, Bayesian statistics, and deep learning to improve the transparency and reliability of AI's reasoning capabilities. PlantingSpace's approach involves developing a universal language for representing heterogeneous information and employing a visual and natural language representation to make reasoning processes understandable. The company provides their AI services in various domains, acting as research assistants, analysts, or data scientists, and focuses on harnessing cutting-edge AI techniques to enhance analysis and problem-solving.
📋 Description
• 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
🎯 Requirements
• Software Engineers with a Bayesian statistics background • 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
🏖️ Benefits
• Our team works fully remotely, and mostly within the CET timezone.
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