ML Engineer

1 month ago


London, United Kingdom grasp.study Full time

The Role

We are developing a hyper-personalised learning tool for adults. It’s not a chatbot but language is a critical consideration. Your work would lie at the intersection of knowledge representation, resource recommendation, LLMs, neural IR, and pedagogy. This R&D position focuses on new solutions rather than optimisation. You’ll have a lot of freedom in how you work; you will be told the problems to solve rather than the approaches to take. This is a hybrid office position requiring you to be in London regularly, if not daily. The work is hard but rewarding.

The Company

We are a team of 10 people based in London, England. Our mission is to increase the rate at which humans learn. We are currently in closed beta, iterating with a core group of passionate users, and have recently raised $4M+ from investors including Balderton, Point9, and Mozilla. Grasp is also a member of Makerversity, a pioneering community of over 350 world-leading entrepreneurs, creators and innovators.

Mandatory

  • STEM MSc or higher.
  • 5+ years experience in Machine Learning, in particular Natural Language Processing (PhD counts).
  • Recent, intensive experience in Recommender Systems.
  • You are well versed in how to leverage large language models in your area of expertise.
  • A track record of framing problems, prototyping solutions, and integrating them into larger systems.
  • Professional – timely, honest, team-player etc.

Desirable

  • STEM PhD.
  • Research publications or presentations.
  • Startup experience.
  • Long term member of a research community (meetup/signal/telegram groups etc.) in relevant/adjacent fields.
  • Experience in any of the following: GNNs, neural IR, knowledge distillation, semantic networks.

Signs that you might be the right person

  • You enjoy working on hard problems.
  • You can learn new areas quickly and thoroughly.
  • People tell you that you can explain difficult things in a simple way.
  • You think you have a good sense of what’s “good enough”.
  • You have a reputation for getting stuff done.
  • You’re a curious person.
  • Sign-on stock options bonus designed for the long term.
  • A* colleagues with backgrounds at top firms.
  • A mission you care about.
  • In contact with reality (everything is linked to the user).
  • Nice office environment.
  • Great technology/kit budget.
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