We’re building the one place for accurate information on the web. In our decentralized platform, accurate information always wins against other noises. Current approaches to determine accuracy don’t work ‒ AI is still ineffective in reasoning, and naive human moderation is biased and not scalable. We are building a novel approach that combines the power of ML/NLP (to rigorously deconstruct discourses) and probabilistic graphical models (PGM) (to drive collective behaviors towards reason at scale), with intuitive and highly usable UX.
We are currently still in stealth mode, with a product in alpha stage and sufficient funding, backed by experienced entrepreneurs, media veterans, and a deeply technical team in software engineering, machine learning, and mathematical sciences. The current team of full-timers and part-timers hails from NTU, NUS, Stanford, Harvard, and other top institutions. The team is currently distributed across three continents, with the tech team mostly based in Singapore.
As a backend software engineer (on-site or remote) you will be responsible for designing, developing, testing, and deploying high performance, efficient, and scalable systems, such as content systems, identity systems, reputation systems, consensus mechanisms, content or topic recommender systems, search systems, etc. You might also help build and maintain common libraries and frameworks in our codebase.
If you choose to, you can also do full-stack development across our React.js-based frontend and Go backend. If you are interested in machine learning or data engineering, you can also choose to do software projects in the intersection of large scale systems and machine learning or data engineering.
You will work with some of our experienced engineers in the team who have many years of experience building large scale systems, and you will participate in product planning, design review, and code review process. You will also have the opportunity to shape our engineering standards, processes, and common libraries and tools.
Qualifications:
* Strong computer science fundamentals with a top tier educational background in Computer Science or other quantitative majors
* Strong understanding of algorithms and data structures
* Strong logic and abstraction ability, preferably with familiarity of how software works across the technology stack (network, memory, disk)
* Experience with MVC libraries and microservice practices
* Knowledge of a few programming languages, preferably Java, Go, Rust, or C++
* Good engineering practices (design, coding, testing, tooling)
* Good sense of ownership and a strong learning ability
Job Type
Salary
Status
Closing Date
