RequirementsThe ideal candidate demonstrates:
- domain expertise in either machine learning or formal methods; interest in learning the other if expertise is in one of these
- fast learning of deep technical subjects
- experience running machine learning experiments, ideally at scale
- experience with post-training large language models
- knowledge of software engineering best practices (advanced git workflows, testing, containerization, code reviews, etc)
- familiarity with MLOps tools, working models on multi-GPU clusters
- an understanding of specification-aware programming (Dafny, Viper) and proof assistants (LEAN, Isabel)
- experience using AI-assisted or AI-accelerated programming (Cursor or similar)
and/or a willingness and ability to learn and grow in any of the above areas and beyond.
Benefits- Competitive salary
- Equity (through share option scheme)
- Flexible working patterns
- Healthcare, childcare, fitness and other common benefits (we're figuring this out)
- Being there from the very early stages
