POSITION SNAPSHOT:
Our client is a pioneering AI company dedicated to transforming manufacturing processes through a “small data” approach to AI. In this role, you will be the first dedicated ML Research Engineer, responsible for building core AI capabilities that will directly impact manufacturing efficiency and sustainability at scale. You’ll work in a remote-first, collaborative environment, pioneering practical AI solutions that put an expert operator next to each industrial machine.
Key duties include collaborating on strategic technical decisions, rapidly prototyping and iterating on AI solutions, and developing and implementing Bayesian Optimisation algorithms that suggest batches of experiments. You will also implement knowledge transfer capabilities across machines and create robust data quality systems.
The role requires a strong understanding of optimisation under uncertainty and multi-objective optimisation, and you will occasionally engage directly with manufacturing customers to understand real-world constraints. Candidates should have a strong expertise in Bayesian Optimisation and Gaussian Processes (theory and practical), hands-on experience with Few-Shot Learning, and a solid background in statistics and experimental design.
The position requires advanced proficiency in Python and libraries like sklearn and GPflow, a Manufacturing background, along with a startup mindset that prioritises practical, deployable solutions over theoretical approaches. The ideal candidate will be motivated by solving real-world problems with tangible industrial impact and be comfortable with ambiguity and rapid priority changes.
Remote role, competitive salary, Bonus, Share/equity options.
Position Snapshot is a summary of the role. Full job description is available from the client