Computer Vision Engineer

Capua
Nottingham
1 year ago
Applications closed

Related Jobs

View all jobs

Computer Vision Engineer

Senior Data Research Engineer Computer Vision

Senior Computer Vision Engineer - up to £70,000 - ID44602

Senior Computer Vision Engineer

Senior Computer Vision Engineer

Senior Computer Vision Engineer...

Cutting edge financial technology scale-up | Computer Vision Engineer | Remote | £45-60K DOE + bonus


About the Company:

Our partner is a pioneering financial technology company that empowers organisations to leverage agent-based modelling, AI, and machine learning to make more informed decisions and drive growth. Their clients include global banks, regulators, and exchanges. Founded in 2016, the company has rapidly expanded since graduating from the Barclays TechStars programme in 2017 and Mastercard Start Path in 2018. Their team comprises first-class talent, including PhDs with extensive expertise in financial services and beyond.


About the Role:

Our client is now looking to expand their team and take on a talented Mid-level Engineer with expertise in computer vision. As an Engineer, you will play a key role in developing and applying advanced computer vision techniques to the company's cutting-edge simulation platform. Your main responsibilities would include enhancing their simulation models by integrating computer vision algorithms to improve data collection, object recognition, and analysis in a dynamic, simulated environment as well as designing, testing, and optimizing algorithms related to image processing, object detection, tracking, and analysis within simulation scenarios.


Responsibilities:

  • Integrate computer vision algorithms into simulation models to enhance data collection and analysis.
  • Develop and optimize image processing algorithms for object detection, tracking, and recognition within simulations.
  • Collaborate with AI/ML teams to apply computer vision for intelligent system behavior and predictive analytics.
  • Innovate new applications for computer vision in simulations, such as autonomous vehicles, robotics, or smart cities.
  • Enhance simulation software tools to support advanced visual data processing and improve user experience.
  • Provide technical support for integrating visual data from cameras or sensors into the simulation environment.


Requirements:

  • Bachelor's or Master’s degree in Computer Science, Engineering, or a related field.
  • 2+ years experience in computer vision, including image processing, object detection, tracking, and pattern recognition.
  • Strong programming skills in languages such as Python, C++, or Java, with familiarity in computer vision libraries like OpenCV, TensorFlow, or PyTorch.
  • Experience with machine learning algorithms and their application in computer vision tasks.
  • Familiarity with simulation technologies or agent-based modelling would be advantageous.
  • Experience working with large datasets and optimizing algorithms for real-time processing.
  • Strong problem-solving abilities, attention to detail, and a passion for working on innovative, cutting-edge technologies.
  • Ability to work collaboratively in a cross-functional team environment.


Compensation and Benefits:

  • Competitive salary (£45-60K DOE + bonus).
  • Remote working arrangement.
  • Opportunities to take on leadership roles and make an impact in a fast-growing start-up.

Subscribe to Future Tech Insights for the latest jobs & insights, direct to your inbox.

By subscribing, you agree to our privacy policy and terms of service.

Industry Insights

Discover insightful articles, industry insights, expert tips, and curated resources.

Careers Jobs

Machine Learning Jobs for Career Switchers in Their 30s, 40s & 50s (UK Reality Check)

Are you considering a career change into machine learning in your 30s, 40s or 50s? You’re not alone. In the UK, organisations across industries such as finance, healthcare, retail, government & technology are investing in machine learning to improve decisions, automate processes & unlock new insights. But with all the hype, it can be hard to tell which roles are real job opportunities and which are just buzzwords. This article gives you a practical, UK-focused reality check: which machine learning roles truly exist, what skills employers really hire for, how long retraining realistically takes, how to position your experience and whether age matters in your favour or not. Whether you come from analytics, engineering, operations, research, compliance or business strategy, there is a credible route into machine learning if you approach it strategically.

Jobs

How to Write a Machine Learning Job Ad That Attracts the Right People

Machine learning now sits at the heart of many UK organisations, powering everything from recommendation engines and fraud detection to forecasting, automation and decision support. As adoption grows, so does demand for skilled machine learning professionals. Yet many employers struggle to attract the right candidates. Machine learning job adverts often generate high volumes of applications, but few applicants have the blend of modelling skill, engineering awareness and real-world experience the role actually requires. Meanwhile, strong machine learning engineers and scientists quietly avoid adverts that feel vague, inflated or confused. In most cases, the issue is not the talent market — it is the job advert itself. Machine learning professionals are analytical, technically rigorous and highly selective. A poorly written job ad signals unclear expectations and low ML maturity. A well-written one signals credibility, focus and a serious approach to applied machine learning. This guide explains how to write a machine learning job ad that attracts the right people, improves applicant quality and strengthens your employer brand.

Education Jobs

Maths for Machine Learning Jobs: The Only Topics You Actually Need (& How to Learn Them)

Machine learning job adverts in the UK love vague phrases like “strong maths” or “solid fundamentals”. That can make the whole field feel gatekept especially if you are a career changer or a student who has not touched maths since A level. Here is the practical truth. For most roles on MachineLearningJobs.co.uk such as Machine Learning Engineer, Applied Scientist, Data Scientist, NLP Engineer, Computer Vision Engineer or MLOps Engineer with modelling responsibilities the maths you actually use is concentrated in four areas: Linear algebra essentials (vectors, matrices, projections, PCA intuition) Probability & statistics (uncertainty, metrics, sampling, base rates) Calculus essentials (derivatives, chain rule, gradients, backprop intuition) Basic optimisation (loss functions, gradient descent, regularisation, tuning) If you can do those four things well you can build models, debug training, evaluate properly, explain trade-offs & sound credible in interviews. This guide gives you a clear scope plus a six-week learning plan, portfolio projects & resources so you can learn with momentum rather than drowning in theory.

🍪 We use cookies to enhance your browsing experience on our website. By continuing to use this site, you consent to the use of cookies as described in our Cookie Policy. You can review our Cookie Policy for more information.