At a Glance
- Tasks: Design and develop innovative computer vision systems from concept to launch.
- Company: Exciting start-up in Saffron Walden, tackling global challenges with tech.
- Benefits: Competitive salary, dynamic work environment, and potential for career growth.
- Other info: Inclusive recruitment process and opportunities for professional development.
- Why this job: Join a successful team and work on life-saving technology.
- Qualifications: Master's degree or relevant experience in computer vision required.
The predicted salary is between 30000 - 60000 £ per year.
A brilliant opportunity for a Computer Vision Engineer or Masters Graduate to work for an exciting start-up in Saffron Walden, Essex, that is tackling some of the world’s most pressing challenges. The company is founded by a team of brilliant Engineers who have already realised success with other start-ups. This offers the chance to work in an environment filled with technological innovation whilst working on cutting-edge tech. You will apply your knowledge in computer vision systems, from initial design through to product launch. This role is open to both experienced Computer Vision Engineers and Master’s Grads with relevant academic project experience on Computer Vision.
Location: Saffron Walden, on-site
Salary: £30,000 to £60,000 per annum
Requirements for Computer Vision Engineer:
- You will either be educated to PhD level in Computer Vision or a related field, OR hold a Master’s degree with strong academic project experience in computer vision, OR have proven industry experience as a Computer Vision Engineer.
- This company values a solid academic history (i.e. top Uni with good grades throughout, AAA at A Level etc).
- Skilled in building computer vision solutions, with a focus on object detection and motion tracking.
- Knowledgeable in modern machine learning techniques, including convolutional neural networks (CNNs) and transformer models.
- Ideally you’ll have experience with tracking methods, including the use of Kalman filters.
- Aware of traditional, lower-resource image processing techniques such as blob detection.
- Proficient in Python for developing and implementing solutions.
- Any experience in video analysis, optics or working within an agile environment is beneficial.
- Due to the nature of some clients, you must be willing and eligible to qualify for UK Security Clearance.
Responsibilities for Computer Vision Engineer:
- Support the design, testing, and validation of optical hardware, including imaging sensors, optical assemblies, and related components.
- Contribute to the creation of solutions for visual monitoring, tracking, and image analysis.
- Adapt and refine image processing workflows to enhance system efficiency and output quality.
- Work closely with cross-functional teams comprising engineering, technical, and product specialists.
- Design tailored algorithms informed by the latest advancements in computer vision.
- Build robust machine vision systems designed to meet stringent performance and reliability standards.
- Plan and manage tasks effectively to ensure the timely delivery of reliable, well-documented outputs.
- Take part in the development and testing of prototypes through to final product launch.
What this offers:
- An opportunity to join a success story in the making with a team that has realised big success in other start-ups.
- Working on a cutting-edge stack in a highly innovative environment.
- Working on technology that has the potential to save thousands of lives.
Applications:
If you would like to enquire about this unique Computer Vision Engineer opportunity, we would love to hear from you. Please send an up-to-date CV including details of your online repository via the relevant link.
We’re committed to creating an inclusive and accessible recruitment process. If you require reasonable adjustments for your application or during the review process, please highlight this by emailing applications@redtech-recruit.com.
RedTech Recruitment Ltd focuses on finding roles for Engineers and Scientists. Even if the above role isn’t of interest, please visit our website to see our other opportunities. We are an equal-opportunity employer and value diversity at RedTech.
Computer Vision Engineer - Graduate Considered in Essex employer: RedTech Recruitment
Join a dynamic and innovative defence AI firm in Saffron Walden, where you will play a crucial role in shaping the company culture and driving impactful HR practices. With a strong emphasis on collaboration and employee growth, this fast-paced environment offers unique opportunities for professional development and the chance to make a meaningful contribution to the company's success.
StudySmarter Expert Advice🤫
We think this is how you could land Computer Vision Engineer - Graduate Considered in Essex
✨Tip Number 1
Network like a pro! Reach out to your connections in the tech world, especially those in computer vision. Attend meetups or webinars, and don’t be shy about asking for introductions. You never know who might have the inside scoop on job openings!
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects, especially those related to computer vision. Whether it’s GitHub repos or a personal website, make sure potential employers can see what you can do. It’s all about making a strong impression!
✨Tip Number 3
Prepare for interviews by brushing up on your technical knowledge. Be ready to discuss your experience with object detection, motion tracking, and machine learning techniques. Practise coding challenges and be prepared to explain your thought process during problem-solving.
✨Tip Number 4
Apply through our website! We’ve got loads of opportunities that might just be perfect for you. Plus, applying directly shows your enthusiasm and commitment. Don’t miss out on the chance to join an innovative team tackling real-world challenges!
We think you need these skills to ace Computer Vision Engineer - Graduate Considered in Essex
Some tips for your application 🫡
Tailor Your CV:Make sure your CV is tailored to the Computer Vision Engineer role. Highlight relevant projects, skills, and experiences that align with the job description. We want to see how your background fits into our innovative environment!
Showcase Your Projects:Include details about your academic projects or any personal work related to computer vision. If you’ve got an online repository, link it! This gives us a chance to see your practical skills in action.
Be Clear and Concise:When writing your application, keep it clear and to the point. Use straightforward language and avoid jargon unless it’s relevant. We appreciate a well-structured application that’s easy to read!
Apply Through Our Website:Don’t forget to apply through our website! It’s the best way for us to receive your application and ensures you’re considered for this exciting opportunity. We can’t wait to hear from you!
How to prepare for a job interview at RedTech Recruitment
✨Know Your Tech
Make sure you brush up on your knowledge of computer vision systems, especially object detection and motion tracking. Be ready to discuss any relevant academic projects or experiences you've had with convolutional neural networks (CNNs) and Kalman filters.
✨Showcase Your Problem-Solving Skills
Prepare to talk about how you've tackled challenges in your previous projects. Think of specific examples where you adapted image processing workflows or designed algorithms that improved system efficiency. This will show your potential employer that you're not just knowledgeable but also practical.
✨Familiarise Yourself with the Company
Research the start-up and its founders. Understanding their previous successes can help you align your answers with their values and goals. Plus, it shows genuine interest in the role and the company, which is always a plus!
✨Practice Your Communication Skills
Since you'll be working closely with cross-functional teams, it's crucial to demonstrate your ability to communicate complex ideas clearly. Practice explaining your past projects in simple terms, focusing on your contributions and the impact they had on the overall project.
