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- Tasks: Drive the development of cutting-edge computer vision models for real-time retail execution.
- Company: Join Neurolabs, a leader in innovative retail technology.
- Benefits: Competitive salary, equity options, hybrid work, and generous leave.
- Why this job: Be part of transforming retail with impactful technology and real-world results.
- Qualifications: PhD or equivalent in Computer Vision, strong Python skills, and experience with CV models.
- Other info: Collaborative culture with opportunities for personal and professional growth.
The predicted salary is between 72000 - 108000 £ per year.
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.
Why this role matters
In-store execution is broken – slow, manual, outdated. We\’re fixing that.
Our values & how we work
- 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.
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Staff Computer Vision Engineer employer: Neurolabs
Contact Detail:
Neurolabs Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Staff Computer Vision Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, and connect with people on LinkedIn. You never know who might have the inside scoop on job openings or can refer you directly.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to computer vision. This is your chance to demonstrate what you can do beyond just a CV.
✨Tip Number 3
Prepare for interviews by practising common questions and technical challenges. Get comfortable explaining your thought process and how you tackle problems – it’s all about showing your approach!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are genuinely interested in joining our mission.
We think you need these skills to ace Staff Computer Vision Engineer
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience in Computer Vision and Machine Learning. We want to see how your skills align with our mission to revolutionise retail execution!
Showcase Your Projects: Include specific examples of your past work, especially any large-scale CV models you've developed. We love seeing real-world applications of your skills, so don’t hold back on the details!
Be Clear and Concise: When writing your application, keep it straightforward and to the point. We appreciate clarity, so make sure your technical expertise shines through without unnecessary jargon.
Apply Through Our Website: We encourage you to submit your application directly through our website. It’s the best way for us to receive your details and ensures you’re considered for this exciting opportunity!
How to prepare for a job interview at Neurolabs
✨Know Your Stuff
Make sure you brush up on your knowledge of computer vision and machine learning. Be ready to discuss your experience with large-scale CV models, especially in production. Familiarise yourself with the latest architectures and frameworks like PyTorch or TensorFlow, as these will likely come up during technical discussions.
✨Showcase Your Problem-Solving Skills
Prepare to share specific examples of how you've tackled challenges in previous projects. Neurolabs is all about fixing broken processes, so think about times when you've improved model performance or streamlined workflows. Highlight your hands-on approach and how you iterate based on evidence.
✨Communicate Clearly
Since you'll be working cross-functionally, practice explaining complex technical concepts in simple terms. Be ready to discuss how your work aligns with business goals and how you can contribute to the team’s success. Clear communication is key, especially when collaborating with non-technical stakeholders.
✨Emphasise Team Collaboration
Neurolabs values teamwork, so be prepared to talk about your experiences working with diverse teams. Share how you've collaborated with product, infrastructure, and customer teams in the past. Show that you're not just a lone wolf but someone who thrives in a collaborative environment.