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Bayesian Software Engineer

Remote Full-time

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Experience Level

Experience

Qualifications

Preferred QualificationsExperience in backend software engineering with a focus on production environments. Proficient in designing and implementing features for probabilistic programming languages. Hands-on experience with Bayesian inference methods, such as MCMC, SMC, or VI. Ability to model real-world statistical scenarios effectively. Familiarity with constrained optimization algorithms. Knowledge of functional or typed programming, with Julia being the primary language for our core system. Familiarity with Rust, OCaml, or Clojure is also beneficial, along with experience in C++ or Haskell.

About the job

At plantingspace, we are pioneering an innovative AI system tailored for analysts and scientists, leveraging a revolutionary approach to reasoning and knowledge representation. Our technology surpasses traditional state-of-the-art LLMs by intricately combining algorithms in a symbolic manner, enabling groundbreaking features such as multi-step analysis, transparent reasoning paths, and uncertainty assessment. We envision our applications transforming research and analysis across various fields, including Finance, Strategy Consulting, Engineering, Material Sciences, and beyond.

We seek passionate Bayesian Software Engineers equipped with a solid background in Bayesian statistics to contribute to the development of our advanced models and algorithms for statistical inference and machine learning. Your role will involve designing, implementing, and optimizing statistical procedures that can be applied to a diverse range of models, all of which will be integrated within our expansive software system.

About plantingspace

plantingspace is at the forefront of AI innovation, dedicated to enhancing analytical capabilities for professionals across multiple disciplines. Our commitment to redefining knowledge representation and reasoning empowers researchers and analysts to achieve unprecedented insights and efficiencies.

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