At a Glance
- Tasks: Design and develop cutting-edge computer vision systems for real-world applications.
- Company: Join AtkinsRéalis, a leader in engineering services and nuclear innovation.
- Benefits: Enjoy competitive salaries, flexible working, and tailored benefits for your lifestyle.
- Other info: Be part of a diverse team committed to creating a better future for our planet.
- Why this job: Make a real impact on modernising infrastructure and enhancing safety with technology.
- Qualifications: Proficient in Python/C++ with experience in computer vision algorithms and model lifecycle management.
The predicted salary is between 30000 - 50000 £ per year.
The nuclear sector is tackling some of the most complex challenges of our time - modernising infrastructure, enhancing safety, and accelerating the transition to low-carbon energy. Our Digital Products and Technology (DP&T) team partners with clients to address these challenges by building secure, scalable solutions that integrate IoT, robotics, and engineering data.
As a Computer Vision Engineer, you will contribute to the design, development, and deployment of production-grade computer vision systems, supporting both intelligence generation and autonomous action. You will work in multidisciplinary teams alongside engineers, consultants, and domain experts, transforming complex technical problems into robust, reusable, and maintainable solutions with real-world impact.
Your role
- You will be involved across the full computer vision lifecycle, from problem definition through to deployment and continuous improvement.
- Problem framing & solution design: Translate product, robotics, or inspection needs into well-scoped computer vision tasks and end-to-end processing pipelines.
- Data pipelines: Plan and execute data collection, curation, augmentation, and annotation strategies for computer vision datasets.
- Modelling & algorithms: Implement, adapt, and fine-tune computer vision models and methodologies, spanning both 2D and 3D techniques.
- Model & pipeline evaluation: Define and implement appropriate performance metrics (accuracy, robustness, latency, efficiency) and carry out structured error and failure-mode analysis.
- Optimisation & deployment: Optimise models and pipelines for deployment on edge and accelerated platforms, balancing accuracy, latency, resource usage, and reliability.
- Integration & productionisation: Build and maintain production-grade inference and processing services suitable for diverse deployment environments. Use version control, CI/CD, and dataset/model versioning to support reproducible and maintainable delivery.
About You
- Proficient in Python and/or C++ with hands-on experience with tools such as PyTorch and OpenCV.
- Understanding and proven experience utilising a wide range of computer vision algorithms including:
- Classical deterministic image processing.
- 2D based deep learning including object detection and similar processes.
- 3D scene reconstruction and spatial reasoning.
- Image translation alignment and warping.
- Standard 2D imagery (colour and grayscale).
- Depth sensing technologies.
- Hyperspectral imagery.
- X-ray and gamma imaging.
Bonus Skills That Help You Thrive
- Embedded and edge acceleration, including CUDA, cuDNN, and TensorRT.
- Advanced 3D representations such as NeRFs and Gaussian Splatting.
- Experience with 3D visualisation or simulation engines (e.g. NVIDIA Omniverse, Unity, Unreal).
- Model explainability techniques (e.g. class activation maps).
- CI/CD-based testing of ML and computer vision pipelines.
- Understanding of open-source licensing and its implications in commercial and regulated environments.
Reward & Benefits
Explore the rewards and benefits that help you thrive - at every stage of your life and your career. Enjoy competitive salaries, employee rewards and a brilliant range of benefits you can tailor to suit your own health, wellbeing, financial and lifestyle choices. Make the most of a myriad of opportunities for training and professional development to grow your skills and expertise. And combine our hybrid working culture and flexible holiday allowances to balance a great job and fulfilling personal life.
About AtkinsRéalis
We’re AtkinsRéalis, a world-class engineering services and nuclear organization. We connect people, data and technology to transform the world’s infrastructure and energy systems. Together, with our industry partners and clients, and our global team of consultants, designers, engineers and project managers, we can change the world. We’re committed to leading our clients across our various end markets to engineer a better future for our planet and its people.
Additional Information
This role may require security clearance and offers of employment will be dependent on obtaining the relevant level of clearance. If this is necessary, it will be discussed with you at interview. The vetting process is delivered by United Kingdom Security Vetting (UKSV) and may require candidates to provide proof of residency in the UK of 5 years or longer. We are committed to creating a culture where everyone feels that they belong - a place where we can all be ourselves, thrive and develop to be the best we can be. So, we offer a range of family friendly, inclusive employment policies, flexible working arrangements and employee resource groups to support all employees. As an Equal Opportunities Employer, we value applications from all backgrounds, cultures and ability.
Computer Vision Engineer in Bristol employer: Energy Job Search
Contact Detail:
Energy Job Search Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Computer Vision Engineer in Bristol
✨Tip Number 1
Network like a pro! Reach out to folks 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 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 those interviews! Brush up on common technical questions related to Python, C++, and computer vision algorithms. Practising with mock interviews can help you feel more confident and ready to impress.
✨Tip Number 4
Apply through our website! We make it super easy for you to find and apply for roles that match your skills. Plus, it shows you're genuinely interested in joining our team at StudySmarter!
We think you need these skills to ace Computer Vision Engineer in Bristol
Some tips for your application 🫡
Tailor Your Application: Make sure to customise your CV and cover letter to highlight your experience with computer vision, Python, and C++. We want to see how your skills align with the specific challenges we face in the nuclear sector.
Showcase Your Projects: Include examples of your past work, especially any projects involving computer vision algorithms or data pipelines. This gives us a clear picture of your hands-on experience and problem-solving abilities.
Be Clear and Concise: When writing your application, keep it structured and to the point. Use bullet points for key achievements and make sure your technical documentation skills shine through. We appreciate clarity!
Apply Through Our Website: Don’t forget to submit your application through our website! It’s the best way for us to receive your details and ensures you’re considered for the role. Plus, it’s super easy!
How to prepare for a job interview at Energy Job Search
✨Know Your Tech Inside Out
Make sure you brush up on your Python and C++ skills, especially with tools like PyTorch and OpenCV. Be ready to discuss specific algorithms you've used in the past, such as object detection or 3D scene reconstruction, and how they relate to the role.
✨Showcase Your Problem-Solving Skills
Prepare to talk about how you've tackled complex computer vision challenges before. Think of examples where you defined problems, designed solutions, and iterated on models. This will demonstrate your ability to contribute to the full computer vision lifecycle.
✨Be Ready for Technical Questions
Expect questions about data pipelines, model evaluation, and optimisation techniques. Brush up on performance metrics and be prepared to explain how you would balance accuracy and latency in a production environment.
✨Communicate Clearly and Effectively
Since you'll need to produce clear technical documentation, practice explaining your past projects in a way that's understandable to both technical and non-technical audiences. This will show that you can bridge the gap between engineering and stakeholders.