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
3