Bayesian Software Engineering

Program Synthesis Engineering

PlantingSpace

We're building a system that represents domain knowledge as modular probabilistic models — making analysis rigorous and transparent. Users can connect these models flexibly into larger structures. The system enforces consistency across them, and propagates uncertainty through each step. Our first applications are in finance and scientific research, with use cases ranging from equity valuation and distress monitoring, to particle physics. We are looking for strong software engineers to build our program synthesis pipeline. You will be able to choose how close to theory or the production system you want to work, and be exposed to cutting edge research in Bayesian statistics, dynamical systems, information theory, category theory, and more. ESSENTIAL EXPERIENCE * Designing and implementing complex, non-standard algorithms (graph theory, path finding, custom inference, compilers) * Experience in a collaborative, commercial software engineering environment, working on large codebases and using practices like CI/CD, testing, and code reviews USEFUL EXPERIENCE * Implementation of program synthesis frameworks * 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 low level performance optimisation * Mathematics, Computer Science, or Statistics advanced degree 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 * 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 REQUIRED MINDSET We've found that our successful team members share some key characteristics, and as we've grown our team, these are the qualities we've learned to seek out. We take pride in our strong, collaborative culture, and these core attributes not only reflect our shared values, but can help you evaluate how well you might fit into our team: * A builder at heart: You’re passionate about building things, solving complex problems, and approaching challenges with an entrepreneurial spirit and humility. Your sharp sense of prioritisation gives you a laser focus on delivering results that uplift the entire team, moving us closer to our goal. * Results-driven: You thrive when taking full ownership of tasks, seeing them through from start to finish, and taking accountability for the results. You’re proactive, resourceful, and avoid over-complication - anticipating problems, even in complex, uncertain environments. * Growth mindset: You are intellectually curious, have a critical mind, and seek opportunities to stretch your abilities. You explore the state-of-the-art, you dig deep to truly understand a problem, and question assumptions. * A strong collaborator: You naturally communicate with clarity and purpose, ensuring your ideas and updates are easily understood. You work efficiently, embracing an iterative approach that allows for frequent progress and course correction. You’re open to direct feedback, adapting quickly and using it to improve both your work, and the performance of those around you. * Approaching problems and tasks like a project manager: * You can take a given goal and break it down into smaller parts. * You can solve problems systematically, by yourself as well as collaboratively with others. * You involve others in effective problem-solving sessions because you value getting to the best solution over being right. * You document processes well to ensure others can jump in to collaborate effectively. WANT TO KNOW MORE? On our website you can find more about our team and work culture, as well as example tasks that share some insight into the type of things team members are working on. * What we do: https://planting.space/ * Ways of work: https://planting.space/org/ * Team culture and example tasks: https://planting.space/joinus/ Our team works fully remotely, and mostly within the CET timezone.

Statistics Tutor

xAI

SpaceXAI’s mission is to create AI systems that can accurately understand the universe and aid humanity in its pursuit of knowledge. Our team is small, highly motivated, and focused on engineering excellence. This organization is for individuals who appreciate challenging themselves and thrive on curiosity. We operate with a flat organizational structure. All employees are expected to be hands-on and to contribute directly to the company’s mission. Leadership is given to those who show initiative and consistently deliver excellence. Work ethic and strong prioritization skills are important. All employees are expected to have strong communication skills. They should be able to concisely and accurately share knowledge with their teammates. ABOUT THE ROLE: As an AI Tutor - Statistics Specialist, you’ll play a key role in advancing SpaceXAI's mission by enhancing our AI technologies through high-quality inputs, labels, and annotations using specialized software. You’ll collaborate with our technical team to train models on human interactions, problem-solving, and discussions; refine annotation tools; and select/create challenging problems in statistics to boost performance. All of our AI Tutor roles potentially involve gathering or providing data in text, voice, and video formats, including annotations, audio recordings, or video sessions—tasks with which candidates must be comfortable. RESPONSIBILITIES: * Use proprietary software applications to provide input/labels on defined projects. * Support and ensure the delivery of high-quality curated data. * Play a pivotal role in supporting and contributing to the training of new tasks, working closely with the technical staff to ensure the successful development and implementation of cutting-edge initiatives/technologies. * Interact with the technical staff to help improve the design of efficient annotation tools. * Choose problems from statistical domains that align with your expertise, focusing on areas such as probability theory, inferential statistics, regression modeling, multivariate analysis, stochastic processes, Bayesian methods, experimental design, and data-driven applications where you can confidently provide detailed solutions and evaluate model responses. * Interpret, analyze, and execute tasks based on given instructions. BASIC QUALIFICATIONS: * Must have either (a) a Master’s or PhD in Statistics (or Mathematics with a specialization in statistics or probability) or (b) a medal in an International Math Olympiad (IMO), International Statistical Olympiad, or similar competition. * Proficiency in reading and writing, both in informal and professional English. * Strong ability to navigate various information resources and databases. * Outstanding communication, interpersonal, analytical, and organizational capabilities. * Solid reading comprehension skills combined with capacity to exercise autonomous judgment even when presented with limited data/material. * A strong passion for and commitment to technological advancements and innovation. PREFERRED SKILLS AND EXPERIENCE: * PhD in Statistics or a closely related quantitative field. * Peer-reviewed publications in statistics, probability, or applied statistical modeling. * Previous AI Tutoring experience and/or experience teaching college-level statistics courses. LOCATION AND OTHER EXPECTATIONS: * Tutor roles may be offered as full-time, part-time, or contractor positions, depending on role needs and candidate fit. * For contractor positions, hours will vary widely based on project scope and contractor availability, with no fixed commitments required.  On average most projects may involve at least 10 hours per week to achieve deliverables effectively though this is not a fixed commitment and depends on the scope of work. Contractors have full flexibility to set their own hours and determine the exact amount of time needed to complete deliverables.  * Tutor roles may be performed remotely from any location worldwide, subject to legal eligibility, time-zone compatibility, and role specific needs. * For US based candidates, please note we are unable to hire in the states of Wyoming and Illinois at this time. * We are unable to provide visa sponsorship. * For those who will be working from a personal device, your computer must be a Chromebook, Mac with MacOS 11.0 or later, or Windows 10 or later. COMPENSATION AND BENEFITS: US based candidates: $45/hour - $75/hour depending on factors including relevant experience, skills, education, geographic location, and qualifications. International candidates: Information will be provided to you during the recruitment process. Benefits vary based on employment type, location and jurisdiction. Benefits for eligible U.S. based positions include health insurance, 401(k) plan, and paid sick leave. Specific details and role specific information will be provided to you during the interview process. SpaceXAI is an equal opportunity employer. For details on data processing, view our Recruitment Privacy Notice.

Applied Category Theory Research

PlantingSpace

We're building a system that represents domain knowledge as modular probabilistic models — making analysis rigorous and transparent. Users can connect these models flexibly into larger structures. The system enforces consistency across them, and propagates uncertainty through each step. Our first applications are in finance and scientific research, with use cases ranging from equity valuation and distress monitoring, to particle physics. We use category theory to reason about our system end-to-end: from natural language processing and knowledge representation to probabilistic programming and our user interface. We are currently hiring for an Applied Category Theory Researcher to help us research and develop our category theoretic representations of real world phenomena. USEFUL EXPERIENCE * PhD (or equivalent research experience) which involved category theory * Programming in some functional or statically typed programming languages, e.g. Rust, OCaml, Clojure, C++, or Haskell * Writing about category theory in accessible ways * Theory building in computer science, applied mathematics or statistics * Familiarity with some of the listed concepts: * (Logical) foundations of computation * Synthetic probability theory * Probabilistic graphical models (including Bayesian networks) * Denotational semantics * String diagrams, monoidal categories, optics, lenses RESPONSIBILITIES * Follow existing literature and bring up relevant ideas * Formalize the categorical semantics of our probabilistic DSL, feeding back theoretical insights for the benefit of the implementation * Develop new models for real world phenomena along our framework, for example, relationships, probabilistic models, dynamical systems, and natural language * Present results of your work in a way accessible to experts in other fields REQUIRED MINDSET We've found that our successful team members share some key characteristics, and as we've grown our team, these are the qualities we've learned to seek out. We take pride in our strong, collaborative culture, and these core attributes not only reflect our shared values, but can help you evaluate how well you might fit into our team: * A builder at heart: You’re passionate about building things, solving complex problems, and approaching challenges with an entrepreneurial spirit and humility. Your sharp sense of prioritisation gives you a laser focus on delivering results that uplift the entire team, moving us closer to our goal. * Results-driven: You thrive when taking full ownership of tasks, seeing them through from start to finish, and taking accountability for the results. You’re proactive, resourceful, and avoid over-complication - anticipating problems, even in complex, uncertain environments. * Growth mindset: You are intellectually curious, have a critical mind, and seek opportunities to stretch your abilities. You explore the state-of-the-art, you dig deep to truly understand a problem, and question assumptions. * A strong collaborator: You naturally communicate with clarity and purpose, ensuring your ideas and updates are easily understood. You work efficiently, embracing an iterative approach that allows for frequent progress and course correction. You’re open to direct feedback, adapting quickly and using it to improve both your work, and the performance of those around you. * Approaching problems and tasks like a project manager: * You can take a given goal and break it down into smaller parts. * You can solve problems systematically, by yourself as well as collaboratively with others. * You involve others in effective problem-solving sessions because you value getting to the best solution over being right. * You document processes well to ensure others can jump in to collaborate effectively. WANT TO KNOW MORE? On our website you can find more about our team and work culture, as well as example tasks that share some insight into the type of things team members are working on. * What we do: https://planting.space/ * Ways of work: https://planting.space/org/ * Team culture and example tasks: https://planting.space/joinus/ Our team works fully remotely, and mostly within the CET timezone.