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Staff Computer Vision Engineer

Neurolabs
London
1 week ago
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Help us build the future of real-time retail execution

At Neurolabs, we’re helping the world’s leading CPG brands unlock real-time visibility in retail. Our Image Recognition technology is powered by synthetic data and digital twins, giving customers scalable, accurate insights — fast. No manual audits. No delays. No retraining. Just immediate visibility into what’s actually happening in-store.

We’ve built our platform to solve real field problems. From faster SKU onboarding to better promo execution, we work across teams to connect strategy with shelf reality. With easy integration and the fastest time to value in the category, we’re not just digitising audits - we’re powering smarter, data-backed execution for global CPGs.

We’re looking for a Staff Computer Vision Engineer to join our team and play a key role in scaling our vision AI product into a robust, performant, production-grade system. You’ll bring deep technical experience, scientific rigour and a product-aware mindset to the table. This is a role for someone who loves solving tough problems, staying hands-on and helping shape how a team works and wins together.

✨ Why this role matters

In-store execution is broken - slow, manual, outdated. We're fixing that.

At the core of our platform is a Computer Vision engine powered by synthetic data, large vision models and smart pipelines. We're moving fast, solving hard problems and scaling globally. You’ll be central to how we grow and evolve this function.

Your mission: turn complex vision problems into practical, scalable solutions.

💡 Our values & how we work

We’re a tight-knit team who:

  • Move fast and learn continuously – We iterate quickly and hold a high bar for quality.
  • Focus on outcomes – We care about real-world results for our customers and we do this by owning the initiative, staying open and honest.
  • Play to win – We’re building something meaningful with our customers and we want to be the best at it.

🧠 What you'll do

Drive applied model development from idea to deployment

    • Lead the design, training, and optimisation of CV models across detection, recognition, segmentation and tracking tasks.
    • Balance performance, latency, and reliability to ensure models work in dynamic retail environments and across varied shelf conditions.
    • Advance our synthetic data generation pipeline - scaling diversity, improving generalisation and applying domain adaptation strategies that boost robustness.

Own the evolution of our large vision model (LVM) efforts

    • Improve the performance, reliability, and scalability of our in-house LVM - shaping it into a best-in-class system.
    • Help design and deploy a highly generalisable LVM tailored for retail, balancing size, speed and adaptability across real-world use cases.

Stay close to the science and ship what works

    • Test new approaches rigorously, validate performance, and productionise what’s effective.
    • Use PyTorch (or similar frameworks) for fast, iterative experimentation.
    • Contribute to model evaluation, benchmarking and continuous improvement.

Work cross-functionally, without managing people

    • Collaborate with Product, Infrastructure, and Customer teams to deliver models that integrate seamlessly into field workflows.
    • Align technical direction with business goals and guide thinking through technical leadership — no line management required.

Champion practical engineering and good data practices

    • Ensure clean, reliable and well-managed data sits at the heart of all model development.
    • Contribute to scalable MLOps and automation systems that keep deployment smooth and experimentation fast.

Requirements

Experience & technical skills

  • PhD or equivalent experience in Computer Vision, Machine Learning or a related field.
  • Proven track record developing and deploying large-scale CV models in production.
  • Strong programming skills in Python, with hands-on experience in PyTorch or TensorFlow.
  • Deep understanding of modern CV architectures - particularly large vision models and Transformers.
  • Experience with multimodal data (images, video, text) is highly desirable.
  • Experience with MLOps tools and workflows.

How you work

  • You’re hands-on and self-directed, with a strong sense of ownership.
  • You think clearly, test quickly, and iterate based on evidence - not instinct.
  • You care about code quality, model performance, and business value.
  • You collaborate well across functions and share knowledge generously.
  • You communicate technical findings clearly to both technical and non-technical stakeholders.

Benefits

  • Open salary structure - This role offers a competitive salary of up to £150,000 per year.
  • Celebrate our victories together - We’re on an ambitious path and when we succeed, it’s a collective win. You’ll be offered equity share options, allowing you to partake in the value you help build.
  • Hybrid-first approach - We decide together what balance works best between home and our vibrant London office near King’s Cross.
  • A culture of inclusivity - We thrive when we’re authentic with one another, fostering an environment filled with kindness, openness and trust where every voice matters and everyone feels like a vital part of our journey.
  • Time off that suits you - Enjoy a generous 25 days of annual leave along with bank holidays to unwind and recharge.
  • Company retreats - Each year, we take a step back to reflect and reconnect, enjoying some well-deserved social time together.
  • Comprehensive medical insurance - You’ll receive private medical coverage that prioritises both your physical and mental health, including dental, optical and travel insurance.
  • Visa sponsorship available – We can sponsor Skilled Worker visas for eligible candidates who meet UK Home Office requirements.

Please note: We are not accepting unsolicited CVs or candidate introductions from recruitment agencies. Any profiles submitted without prior agreement will be considered the property of Neurolabs, and no fees will be payable.

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