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.
Requirements
Mandatory
- STEM MSc or higher.
- 5+ years experience in Machine Learning, in particular Natural Language Processing (PhD counts).
- Recent, intensive experience in one (or more) of the following: GNNs, recommender systems, neural IR, knowledge distillation, semantic networks.
- 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.
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.
Benefits
- 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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