We are a small London startup with the ambition to change education with ML-powered tutoring. Our flagship product is a mobile application for teaching English to intermediate and advanced learners.

We’re on the verge of solving one of the biggest challenges in education – making high-quality, personalised learning accessible to everyone. We are building a fundamental model for education - one that can accurately predict student knowledge and orchestrate lessons, adapting to the students needs.

We’re looking for a Lead ML Engineer, with a proven track record of delivering ML models to production, to own the ML team in our growing company.

What you will do 🚀

• Build fundamental models for education - solving the ultimate learning task of predicting student knowledge and optimal ‘next task’
• Work with a vast amount of unique data - we have data from over 1M language tests, including text and voice data
• Create brand new dictionaries, applicable to any context - right now it’s the English language, but in the future it could be other languages or even subjects such as Mathematics
• Analyse large amounts of diverse data - including data from every movie, book, and song
• Work in a cross-functional team and communicate with backend engineers and product managers
• Create new types of tests for language learners to gather more test results, analyse them, and build prediction models based on these results
• Optimise and fine-tune machine learning models for performance, scalability, and accuracy
• Lead our ‘AI Powered Education’ meet-up in London, building a network of ML specialists

Essential skills 🙏

• Experience leading and mentoring other ML engineers
• Complete end-to-end experience - from finding and cleaning data all the way to monitoring models in production
• Experience taking complete ownership of entire ML systems and data pipelines in large-scale production systems
• Experience building automated data pipelines
• Strong understanding of CI/CD pipelines and automation tools for efficient model deployment and monitoring
• Strong understanding of neural networks, CNNs, RNNs, LSTMs, and transformers
• Great knowledge of NLP algorithms