ML Engineer - London, United Kingdom - Grasp

Description

The RoleWe 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 CompanyWe 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.
RequirementsMandatorySTEM MSc or higher5+ years experience in Machine Learning, in particular Natural Language Processing (PhD counts)

Recent, intensive experience in Recommender SystemsYou are well versed in how to leverage large language models in your area of expertiseA track record of framing problems, prototyping solutions, and integrating them into larger systemsProfessional - timely, honest, team-player etcDesirableSTEM PhDResearch publications or presentationsStartup experienceLong term member of a research community (meetup/signal/telegram groups etc.) in relevant/adjacent fieldsExperience in any of the following:
GNNs, neural IR, knowledge distillation, semantic networksSigns that you might be the right personYou enjoy working on hard problemsYou can learn new areas quickly and thoroughlyPeople tell you that you can explain difficult things in a simple wayYou think you have a good sense of what's "good enough"You have a reputation for getting stuff doneYou're a curious personBenefitsSign-on stock options bonus designed for the long termA* colleagues with backgrounds at top firmsA mission you care aboutIn contact with reality (everything is linked to the user)Nice office environmentGreat technology/kit budget