Model ML
Member of Technical Staff - Frontend
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Company Overview:
Model ML is the AI workflow builder transforming how major financial institutions produce and validate client-ready work. Model ML converts complex, manual processes into fully automated AI systems that scale across global teams. In under a year, Model ML has become one of the fastest growing enterprise AI platforms worldwide and recently closed a $75 million Series A, one of the largest fintech Series A rounds ever. The round was backed by FT Partners, Y Combinator, LocalGlobe, QED, 13books, and other top global investors, bringing total funding to $90 million.
About The Role:
We are seeking an experienced Front-End Engineer to own the front-end craft bar across our product. This role is ideal for someone who cares about how software actually feels to use, and who would rather set the standard than work to someone else's. You will report to the Head of Engineering, based in London.
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Model ML runs a genuinely full-stack engineering culture and every engineer ships UI. As agentic tooling absorbs more of the day-to-day implementation, the highest-leverage front-end work has moved upstream: defining the patterns everyone codes against, setting the rules the agents work within, and making sure quality scales at the pace the company is moving.
Responsibilities
- 5+ years experience and deep front-end fundamentals, with real curiosity across the wider landscape. You have experience with frameworks and tools beyond React and Next.js, even if only in your own time, and can articulate the trade-offs.
- A clear understanding of what is happening under the hood, rather than reaching for a library the moment something looks hard.
- Serious performance engineering instincts. You can explain why something is slow, not just that it is.
- Strong TypeScript experience.
- Strong architecture and systems design judgement.
- Obsessive attention to detail.
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Requirements
- Own the front-end architecture and pattern library that the whole engineering team codes against.
- Define the guidelines, constraints and review gates that agentic tooling works within, so generated code stays consistent with the system.
- Own front-end performance across dense, information-heavy views rendering large datasets alongside live agent output.
- Set and hold the review bar for front-end work, and turn recurring feedback into documented patterns.
- Maintain the component library and design system alongside design, including the branding layer that makes output client-ready.
- Make framework and tooling decisions, and be able to defend the trade-offs to the engineers who live with them.
- Ship features end to end, from interaction detail through to production support.
- Mentor engineers whose primary discipline is not front-end.
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