At a Glance
- Tasks: Design and develop advanced computer vision systems for the construction industry.
- Company: Join Depixen, a cutting-edge tech company transforming construction with AI.
- Benefits: Competitive salary, flexible working hours, and opportunities for professional growth.
- Other info: Collaborative environment with a focus on innovation and career advancement.
- Why this job: Make a real impact by turning visual data into intelligent decisions in construction.
- Qualifications: Bachelor's degree in relevant field and 3-6 years of computer vision experience.
The predicted salary is between 60000 - 80000 € per year.
About the Role
This role is based at Depixen’s London Office. Depixen is a London-based technology company building the digital decision infrastructure of the construction industry. As a corporate member of the World Wide Web Consortium (W3C), Depixen develops W3C-compliant Linked Data architectures, domain-specific ontologies, taxonomy models, RDF-based data structures, and knowledge graph infrastructures for the construction sector. Through its AI projects with respected universities and institutions in the United Kingdom, Depixen continues to build a scalable global structure across the United States, Europe, and the Far East.
Computer vision is one of the critical perception layers of this infrastructure. In construction, architecture, and building products, visual data is not merely unstructured; it is deeply contextual. Product images, technical documents, drawings, site photos, spatial data, material surfaces, and building elements must be interpreted together with verified technical knowledge, semantic classifications, and machine-interpretable data models. This is not a conventional image recognition role. You will help connect visual AI outputs with verified data, taxonomy, ontology, RDF, and knowledge graph layers, turning perception into reliable decision intelligence for the construction industry.
We are seeking a talented Computer Vision Engineer to design, develop, and productionize advanced perception systems for real-world construction industry use cases. In this role, you will work on object detection, segmentation, OCR, visual matching, product recognition, building element analysis, site image interpretation, video analytics, and multimodal vision-language applications. The ideal candidate is analytical, research-driven, collaborative, and capable of turning advanced computer vision ideas into reliable production systems that address real industry problems.
Responsibilities
- Design, develop, and evaluate robust, scalable, and verifiable computer vision models and pipelines using modern deep learning frameworks.
- Build and optimize end-to-end vision systems covering data preprocessing, model development, deployment, monitoring, and continuous improvement.
- Develop systems for object detection, segmentation, tracking, OCR, image classification, visual matching, product recognition, and video analytics as required.
- Collaborate with data and modelling teams to connect visual AI outputs with taxonomy, ontology, RDF, and knowledge graph layers.
- Work with cross-functional teams to understand product requirements and translate them into scalable technical solutions.
- Develop automated testing, benchmarking, and evaluation workflows to ensure the performance, reliability, and safety of computer vision applications.
- Optimize models and inference pipelines for scalability, latency, and cost-efficiency across GPU and CPU environments.
- Contribute to dataset design, annotation processes, data quality validation, and tools that improve model performance and reliability.
- Translate research-level computer vision and multimodal AI approaches into production-ready technical solutions.
Required Qualifications
- Bachelor’s degree in Computer Science, Electrical Engineering, Computer Engineering, Artificial Intelligence Engineering, or a related field.
- 3-6 years of experience in computer vision, deep learning, or a related AI field.
- Strong proficiency in Python.
- Hands-on experience with deep learning frameworks such as PyTorch, TensorFlow, or similar.
- Practical experience developing, testing, and deploying computer vision models in production environments.
- Solid technical understanding of convolutional and transformer-based architectures, such as CNNs, ViT, YOLO, and Detectron2.
- Hands-on experience in several of the following areas: object detection, segmentation, OCR, tracking, image classification, or video analytics.
- Experience with ML Ops practices and tools such as Docker, Kubernetes, MLflow, and Weights.
AI Engineer [Computer Vision] employer: Depixen
Depixen is an exceptional employer, offering a dynamic work environment in the heart of London where innovation meets collaboration. Employees benefit from a culture that prioritises professional growth through engaging AI projects with leading universities, alongside opportunities to develop cutting-edge computer vision technologies that directly impact the construction industry. With a commitment to W3C-compliant practices and a focus on building a scalable global structure, Depixen provides a unique platform for engineers to thrive and make meaningful contributions in a rapidly evolving field.
StudySmarter Expert Advice🤫
We think this is how you could land AI Engineer [Computer Vision]
✨Tip Number 1
Network like a pro! Reach out to people in the industry, attend meetups, and connect with professionals 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 computer vision projects. Whether it's GitHub repos or a personal website, having tangible examples of your work can really set you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge and problem-solving skills. Practice common interview questions related to AI and computer vision, and be ready to discuss your past projects in detail.
✨Tip Number 4
Don’t forget to apply through our website! We’re always on the lookout for talented individuals like you. Keep an eye on our careers page for the latest opportunities and make sure your application stands out!
We think you need these skills to ace AI Engineer [Computer Vision]
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the AI Engineer role. Highlight your experience with computer vision, deep learning frameworks, and any relevant projects you've worked on. We want to see how your skills align with what we're looking for!
Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Use it to explain why you're passionate about computer vision and how you can contribute to our mission at Depixen. Be sure to mention specific experiences that relate to the job description.
Showcase Your Projects:If you've worked on any cool projects related to object detection, segmentation, or video analytics, make sure to include them in your application. We love seeing practical examples of your work and how you've tackled real-world problems.
Apply Through Our Website:We encourage you to apply through our website for a smoother application process. It helps us keep everything organised and ensures your application gets the attention it deserves. Plus, it's super easy!
How to prepare for a job interview at Depixen
✨Know Your Tech Inside Out
Make sure you’re well-versed in the latest computer vision technologies and frameworks like PyTorch and TensorFlow. Brush up on your understanding of convolutional and transformer-based architectures, as these will likely come up during technical discussions.
✨Showcase Real-World Applications
Prepare to discuss specific projects where you've developed or deployed computer vision models. Highlight how your work has solved real industry problems, especially in construction or related fields, to demonstrate your practical experience.
✨Collaborate Like a Pro
Since this role involves working with cross-functional teams, be ready to talk about your collaborative experiences. Share examples of how you’ve worked with data and modelling teams to connect visual AI outputs with taxonomy and ontology layers.
✨Ask Insightful Questions
Prepare thoughtful questions about Depixen’s projects and their approach to AI in the construction industry. This shows your genuine interest in the role and helps you understand how you can contribute to their goals.
