Product Software Engineering – Quantitative Modeling

Job not on LinkedIn

Likely ghost job

🕒 December 17, 2025

🇺🇸 United States – Remote

⏰ Full Time

🟡 Mid-level

🟠 Senior

🧑‍💻 Full-stack Engineer

👻 Ghost score 68%

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Logo of PlantingSpace

PlantingSpace

11 - 50 employees

🤖 Artificial Intelligence

☁️ SaaS

🏢 Enterprise

💰 Seed Round on 2021-11

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

• Work with product team to define new features • Define implementation strategies, and work with others to implement them • Deliver defined features with a user oriented mindset • 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

• Experience in turning research software into product • Applied mathematical modeling in finance and/or scientific applications • Experience in a collaborative, commercial software engineering environment, working on large codebases and using practices like CI/CD, testing, and code reviews • Strong foundation in computer science algorithms and data structures • Julia, or usage of some more functional or typed languages, e.g. Rust, OCaml, Clojure, C++, or Haskell • Profiling and performance optimisation • Mathematics, Computer Science, or Statistics advanced degree

🏖️ Benefits

• Our team works fully remotely, and mostly within the CET timezone.

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