Edge AI (Computer Vision) Engineer in London

Edge AI (Computer Vision) Engineer in London

London Full-Time 55000 - 70000 £ / year (est.) Home office (partial)
VivaCity

At a Glance

  • Tasks: Develop and optimise AI traffic systems using cutting-edge computer vision technology.
  • Company: Join VivaCity, a leader in smart city solutions focused on sustainability.
  • Benefits: Competitive salary, flexible working, and opportunities for professional growth.
  • Other info: Dynamic work environment with a focus on community and innovation.
  • Why this job: Make a real impact on transport safety and sustainability with innovative AI solutions.
  • Qualifications: Experience with NVIDIA DeepStream and GStreamer pipelines; passion for learning and collaboration.

The predicted salary is between 55000 - 70000 £ per year.

We are looking for an experienced Computer Vision Engineer to help us make transport safer and greener, who thrives on solving complex problems and collaborating to drive product impact.

About the role

We are looking for a Computer Vision Engineer with experience in NVIDIA’s Edge AI stack to work on our core computer vision pipelines, powering real-time inference used by authorities globally to make informed improvements to traffic systems. In this role, you will develop and maintain the systems that power our AI traffic sensors - improving performance, accuracy, and efficiency across our GStreamer and DeepStream-based pipelines. You will work closely with both researchers and hardware engineers to ensure that models are deployed effectively and run reliably in production. This is a highly impactful engineering role focused on deep technical expertise, where you will own key parts of our vision stack and play a central role in improving performance, scalability, and long-term evolution of our edge AI systems. Your work will substantially improve outcomes for customers, and ultimately road users around the world.

Your time will be spent roughly as follows:

  • 75% - Core Engineering (pushing the boundaries of our DeepStream and GStreamer pipelines, building new features, and deploying new deep learning models)
  • 15% - Reactive debugging and support
  • 10% - Cross-team initiatives (e.g. collaborating with cloud engineers on self-learning algorithms, or building dashboards for surfacing new datasets you’ve developed)

This is a unique opportunity to work at the intersection of AI, hardware, and real-world deployment - improving how thousands of sensors understand and interpret the world, and directly contributing to safer and more sustainable transport systems.

About you

You are a hands-on engineer with experience working on embedded computer vision systems and have a strong interest in how deep learning models perform in real-world environments. You are comfortable working within existing systems and improving them over time - whether that’s optimising performance, simplifying complexity, or making systems more robust. You bring solid experience with NVIDIA’s vision stack and are confident working with GStreamer-based pipelines. You are also open and collaborative, and excited to share your knowledge with others - including engineers from different disciplines or with different levels of experience.

Requirements for the role

  • Experience working with complex and custom NVIDIA DeepStream and GStreamer-based pipelines in production (e.g. nvargus, nvinfer, nvtracker)
  • Proven ability to take ownership of complex vision systems, improving structure, maintainability, and enabling upgrades (e.g. JetPack / platform upgrades)
  • Experience working under edge constraints (latency, compute, memory)
  • Strong understanding of end-to-end video / vision systems, from camera input (incl. Optical performance, ISPs, and tuning) through to model inference and output

Any of the following would further strengthen an application:

  • Proficiency with Golang
  • Experience deploying deep learning models into production, especially with custom layers or kernels
  • Experience with production IoT systems
  • Experience with MLOps practices
  • Experience working in a start-up or scale-up environment
  • Interest in sustainability, transport, or smart cities

You don't need to have done all of these things before, but to excel in this role, you will need to be keen to learn and comfortable working in a dynamic, fast-paced environment. If you're close to what we're looking for, please consider applying. Experience comes in many forms, skills are transferable, and passion goes a long way.

Hiring process

  • 30 minute screening interview.
  • 1.5 hour system design interview where you work together with a VivaCity engineer
  • 1.5 hours final round interview, split into a 45 minute technical experience interview and 45 minute soft skills interview

We know that diverse ideas and perspectives drive innovation and make us better. We are creating an environment where everyone, from any background, can do their best work. We're an equal opportunities employer and all applications will receive consideration for employment without regard to ethnicity, religion, gender, gender identity or expression, sexual orientation, nationality, disability, age, or social background. If you need any reasonable accommodations to help you perform at your best during the application process, please let us know.

About us

At VivaCity, we make cities smarter, safer, and more sustainable. We have over 5,000 AI sensors around the world, gathering real-time anonymous data on transport modes, traffic flow, and travel patterns. This is used to gather actionable insights to support strategic decisions to improve the global transport network. All our solutions are community-centric, using 'privacy by design' principles. Our ultimate goal is to make the European vision of a Smart City - one which makes the city work effectively, for the community. We pride ourselves on a collaborative, open culture that fosters innovation, learning and encourages everyone to do their best work, whilst building a sense of community and collaboration.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

Edge AI (Computer Vision) Engineer in London employer: VivaCity

At VivaCity, we are committed to fostering a collaborative and innovative work culture that empowers our employees to make a meaningful impact on urban transport systems. With flexible hybrid working arrangements based in London, we offer competitive salaries, opportunities for professional growth, and a strong focus on sustainability, making us an excellent employer for those passionate about technology and community-centric solutions.

VivaCity

Contact Details:

VivaCity Recruitment Team

StudySmarter Expert Advice🤫

We think this is how you could land Edge AI (Computer Vision) Engineer in London

Tip Number 1

Network like a pro! Reach out to people in the industry, attend meetups, and connect with potential colleagues on LinkedIn. You never know who might have the inside scoop on job openings or can put in a good word for you.

Tip Number 2

Show off your skills! Create a portfolio showcasing your projects, especially those related to computer vision and AI. This will give you an edge and demonstrate your hands-on experience to potential employers.

Tip Number 3

Prepare for interviews by brushing up on your technical knowledge and soft skills. Practice common interview questions and be ready to discuss your past projects in detail. Remember, confidence is key!

Tip Number 4

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 to make transport safer and greener.

We think you need these skills to ace Edge AI (Computer Vision) Engineer in London

Computer Vision
NVIDIA DeepStream
GStreamer
Embedded Systems
Deep Learning
Video Processing
Model Inference

Some tips for your application 🫡

Tailor Your CV:Make sure your CV highlights your experience with NVIDIA’s Edge AI stack and GStreamer pipelines. We want to see how your skills align with the role, so don’t be shy about showcasing relevant projects or achievements!

Craft a Compelling Cover Letter:Your cover letter is your chance to shine! Share your passion for computer vision and how you can contribute to making transport safer and greener. We love seeing enthusiasm and a personal touch in applications.

Showcase Problem-Solving Skills:In your application, give examples of complex problems you've tackled in previous roles. We’re looking for engineers who thrive on challenges, so let us know how you’ve made an impact in past projects!

Apply Through Our Website:We encourage you to apply directly through our website. It’s the best way to ensure your application gets into the right hands. Plus, it shows us you’re keen to join our team at VivaCity!

How to prepare for a job interview at VivaCity

Know Your Tech Inside Out

Make sure you’re well-versed in NVIDIA’s Edge AI stack, especially GStreamer and DeepStream pipelines. Brush up on your knowledge of nvargus, nvinfer, and nvtracker, as these are crucial for the role. Being able to discuss your hands-on experience with these technologies will show that you're ready to hit the ground running.

Showcase Problem-Solving Skills

Prepare to discuss specific examples where you've tackled complex issues in embedded computer vision systems. Think about how you optimised performance or simplified complexity in past projects. This will demonstrate your ability to take ownership of vision systems and improve them over time.

Collaborate and Communicate

Since the role involves working closely with researchers and hardware engineers, be ready to talk about your collaborative experiences. Highlight instances where you shared knowledge or worked cross-functionally. This will show that you’re not just a tech whiz but also a team player who values open communication.

Align with Their Mission

Familiarise yourself with VivaCity’s goals around sustainability and smart cities. Be prepared to express your passion for making transport safer and greener. Showing that you resonate with their mission can set you apart from other candidates and demonstrate your commitment to the role.