Relevance AI

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Graduate Engineer

  • Software Development
  • Full-time
  • Sydney, AU
  • Remote friendly

Relevance AI is a SaaS startup building a platform to help companies and developers leverage machine learning vectors to extract business value from qualitative data like text, images, audio or PDFs. This qualitative unstructured data represents up to 80% of the data businesses generate and store.Our product helps customers create, store, evaluate, search and analyse vector based data sets using AI.

Top companies like Spotify, TikTok, Google utilise vectors and qualitative data to create the most personalised and successful products. We make it easy to use vectors to build the most powerful applications such as NLP Search, Visual Recommendations and help decision makers get a 360 view of their data.

We are looking for a full-time dedicated Graduate Engineer to help build our cutting-edge vector platform that solves big machine learning problems for organisations. You will be joining a rapidly growing VC-backed startup where new ideas and state of the art Machine Learning is applied daily.

More about us

  • We're venture-backed and partnered with one of the biggest global VCs in the space.

  • And we're in the process of bringing on 20+ diverse talent by end of year to join us in our mission.

  • Our Mission: To prepare future thinking business for the era of qualitative data

  • Our Core Values:

    1. Build and Maintain Trust.
      Do what’s right and build trust with teammates, customers and others around you.

    2. Diversity not just in appearance but origin, thinking, hobbies and more.

    3. ChallengeCollaborate and Build.
      Challenge yourself, challenge others and challenge the norm. But don’t just challenge verbally, challenge through actions and through building and collaboration.

    4. Be kind, have fun, and enjoy each other.
      What we are building is hard. The last thing we want is everyone to hate working or each other. So be kind, look out for each other and enjoy.


  • Ability to design accurate and scalable algorithms for creating, storing, evaluating, searching or analysing vectors/deep learning embeddings

  • Ability to analyze and preprocess raw data: assessing quality, cleansing, structuring for downstream processing

  • Ability to be involved in all aspects of a project life cycle, work with clients to illustrate and integrate Relevance AI to generate real business value for them

  • Understanding of Vectors/Deep Learning embeddings and have experience in utilising them for search, recommendations, personalisation, etc

  • Understanding of training Deep Learning models in either Pytorch or Tensorflow (including Convolutional Neural Networks, LSTM, Transformers, Autoencoders, etc)

  • Understanding of traditional statistical modeling: clustering, dimensionality reduction, K-nearest neighbors


  • Confidence in developing backend applications

  • Understanding of multi-threading/processing and asynchronous

  • Understanding of RESTful APIs using frameworks such as Django, FastAPI or Node.js

  • Understanding of source control (Git)


  • Crafting a beautiful and functional frontend application to delight customers.

  • Ability to take ownership of decisions around architecting frontend work such as local state management, testing framework and more.

  • Ability to work closely with the backend and data team to integrate new functionality in a usable way.

  • Ability to work closely with the customer success team to deliver improvements based on feedback.


  • Degree or equivalent experience in quantative field (Statistics, Mathematics, Computer Science, Engineering, etc.)

  • Self starter, take ownership of their work and the quality of it.

  • Open to feedback, new ideas, are able to understand high-level trade-offs at the business and technical level and love solving difficult problems as a team!

Apply now to be an early journey of a startup that will change data as we know it.

Remote restrictions

  • Workday must overlap by at least 6 hours with Sydney NSW, Australia