Highly desirable salary at a quickly scaling startup
A well-backed deep tech startup is hiring an ML Engineer to work on some genuinely unsolved problems in applied computer vision. The team is small, senior, and comes from a mix of top-tier research labs, global tech companies, and leading universities. This is an early hire into a technical team that takes the science seriously.
The problem space
You’ll be building vision models that need to work in the real world – noisy data, scarce labels, wildly variable conditions, and strict compute constraints. The core challenges are around data efficiency, cross-domain generalisation, and running accurate inference on lightweight hardware rather than cloud clusters. Think less “we have a clean benchmark” and more “figure it out from 50 examples and make it work on-device.”
What they need
- Strong PyTorch and clean deep learning engineering habits
- Solid understanding of modern architectures – transformers, VLMs, and beyond
- Grounding in classical signal processing and CV fundamentals
- Experience owning projects end to end, not just modelling in isolation
- Comfortable building custom data pipelines from raw, messy, real-world data
- Edge inference or efficient model deployment experience is a genuine plus
The role
London office, in-person, early-stage team. Suits someone who wants hard technical problems, real ownership, and to build something from scratch rather than maintain what already exists.
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