London | Hybrid | Competitive Salary + Equity
We're building technology for the next generation of autonomous systems, tackling difficult problems across computer vision, ML, sensors, robotics and algorithms .
We're looking for a hands-on Computer Vision / ML Engineer to join our growing AI team and turn ambiguous problems into systems that actually work in the real world.
What you'll be doing
- Computer vision, object detection and tracking
- Sensor fusion and image/signal processing
- ML alongside traditional algorithms
- Optimisation, simulation and autonomy
- Taking ideas from experimentation through to production deployment
- Working directly with engineers and customers to solve real-world problems
What we're looking for
- Strong experience in ML, computer vision or algorithms
- Python plus C++, Rust or Java
- PyTorch, TensorFlow or JAX
- Strong mathematical and problem-solving fundamentals
- MSc/MEng or equivalent technical background
- Experience building and deploying real-world systems
PhDs and publications aren't required — we care about what you can build.
What you'll get
- Competitive salary + meaningful equity
- Free meals and relocation support
- Strong technical team and significant ownership
- Customer-facing work and UK/international travel
- The chance to work on genuinely difficult problems and see your work deployed in the real world
If you enjoy problems where there isn't an obvious answer , this could be a good one.
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Machine Learning Engineer | Computer Vision in London employer: Oho Group
Join a pioneering early-stage AI company in London, where you'll have the unique opportunity to work on foundational technology that shapes how organisations understand and reason over complex information. With a strong emphasis on autonomy and technical influence, you'll be part of a small, highly capable team that values innovative thinking and offers meaningful ownership in the company's success. The collaborative and flexible work culture fosters personal growth and encourages you to turn research ideas into impactful production systems.
