Want to work on the future of AI along a unique approach? Get in touch with us regardless if an open position is listed below. As an early stage startup we are looking to gradually grow our team in the areas of research, software development and operations.

Our compensation is competitive. We believe in co-ownership and aligned incentives, so people can choose to receive cash as well as shares. What matters to us are outcomes, not when and from where you choose to work, so most positions are remote and not bound to any work hours. Nevertheless, we regularly organize physical gatherings to work and have fun together as well.

Check out our team page to learn more about our Ways of Work and Values.

OPEN POSITIONS

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Julia developer

We are looking for top software developers to contribute to development of core components. Work time will be flexible and tasks will focus on general development, stats or optimization. See here for an example task that you could work on.

Useful experience
Backend software engineering
Scientific computing
Julia metaprogramming
Bayesian statistics
Optimization algorithms
Responsibilities
Develop Julia based on clear requirements
Estimate work required for tasks
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Optimization researcher

We are looking for full- or part-time researcher to specify optimization problems and develop algorithms. You will work on interesting theoretical problems with immediate applicability to planning problems for AI.

Useful experience
Developing heuristics for NP-hard problems
Framing optimization problems based on real world situations
Graduate level studies in optimization
Basic category theory
Responsibilities
Formalize optimization problems
Specify relaxations with promising properties
Develop heuristics or approximation algorithms
Prove properties of algorithms
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Inference researcher

We are looking for full- or part-time researcher to design Bayesian inference algorithms in context of our framework. You will work on interesting theoretical problems with immediate applicability to reasoning problems for AI.

Useful experience
Design of Bayesian inference algorithms
Probabilistic modelling
Graduate level studies in statistics
Probabilistc Programming
Bayesian model selection
Responsibilities
Develop inference algorithms
Design convergence diagnostics
Design model selection criteria