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- Tasks: Join our agile team to develop innovative computer vision applications on our Autonomise cloud platform.
- Company: VisionTrack, an award-winning IoT and telematics solution provider.
- Benefits: Competitive salary, flexible working, and opportunities for professional growth.
- Other info: Dynamic environment with a focus on collaboration and cutting-edge technology.
- Why this job: Make a real impact in the exciting field of computer vision and machine learning.
- Qualifications: 2+ years Python experience and knowledge of CNNs and Agile practices.
The predicted salary is between 36000 - 60000 £ per year.
Job Title:
Computer Vision Engineer
About us:
VisionTrack is a multiple award winning IOT, high throughput / big data insurance telematics & video solution.
Role:
We are looking for developers with experience in computer vision applications to join one of our agile development teams. We try to avoid silos of knowledge so the role will involve working in all areas of the solution but with more emphasis on computer vision applications deployed on our Autonomise cloud platform. We are looking for someone who can fit into this way of working, so knowledge in Agile / DevOps working practices, including SCRUM, Continuous Integration & Continuous Delivery and someone who can follow and promote best practices in these areas is essential.
Essential Skills:
- Proficient in Python programming (2+ years’ experience)
- Previous experience in the development and use of Convolution Neural Networks (CNN’s) for machine vision and image analysis applications
- Previous development and fast prototyping experience in at one of following specializations of computer vision or machine learning:
- Object/face/pedestrian detection and tracking
- Activity Recognition
- Camera Calibration
- 3D stereo, SLAM or Depth estimation from video
- Familiarity with SCRUM
- Familiarity with DevOps Continuous Integration / Continuous Delivery practices
- Good written and excellent spoken communication skills as well as attention to detail
Desired Skills:
- MSc or PhD degree in Computer Science, Computer Vision, Machine Learning, Robotics or related technical field
- Python experience
- Experience shipping computer vision solutions or fast prototyping and development
- Strong grasp of latest cutting edge research in object detection, similarity, transfer & few-shot learning
- Experience with using CNN models in production
- Experience using wide range of cameras or camera agnostic solutions
- DevOps CI/CD working / best practices – automation first approach
- Git, including GitFlow & Pull Requests / Peer Reviews
- Working with Geospatial data
- Academic background in a scientific or technical discipline with some formal computer vision / machine learning content
- Publication in Computer vision or machine learning topics
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Computer Vision Engineer employer: VisionTrack
Contact Detail:
VisionTrack Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Computer Vision Engineer
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups or webinars, and connect with people 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, especially those using CNNs or any cool prototypes you've built. This gives potential employers a taste of what you can do and sets you apart from the crowd.
✨Tip Number 3
Prepare for interviews by brushing up on Agile and DevOps practices. Be ready to discuss how you've applied these methodologies in your past work. It’s all about showing that you can fit into their team dynamic!
✨Tip Number 4
Don’t forget to apply through our website! We love seeing applications come directly from candidates who are genuinely interested in joining us at VisionTrack. Plus, it makes it easier for us to keep track of your application.
We think you need these skills to ace Computer Vision Engineer
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with Python and computer vision applications. We want to see how your skills match the job description, so don’t be shy about showcasing your relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Use it to explain why you’re excited about the role and how your background in Agile/DevOps practices makes you a great fit for our team at VisionTrack.
Showcase Your Projects: If you've worked on any cool projects involving CNNs or machine vision, make sure to mention them! We love seeing practical examples of your work, especially if they relate to the technologies we use.
Apply Through Our Website: We encourage you to apply directly through our website. It’s the best way for us to receive your application and ensures you’re considered for the Computer Vision Engineer position!
How to prepare for a job interview at VisionTrack
✨Know Your Tech Inside Out
Make sure you brush up on your Python skills and be ready to discuss your experience with Convolutional Neural Networks. Be prepared to share specific examples of projects where you've implemented computer vision techniques, especially in areas like object detection or activity recognition.
✨Show Off Your Agile Knowledge
Since the role involves working in an Agile environment, it’s crucial to demonstrate your understanding of SCRUM and DevOps practices. Think of examples where you've successfully collaborated in a team setting, and be ready to discuss how you’ve contributed to Continuous Integration and Continuous Delivery processes.
✨Prepare for Practical Challenges
Expect some hands-on challenges during the interview. You might be asked to solve a problem or prototype a solution on the spot. Practise coding problems related to computer vision and be familiar with tools like Docker, as they may come up in discussions.
✨Communicate Clearly and Confidently
Good communication is key! Be clear and concise when explaining your past experiences and technical concepts. Remember, the interviewers are looking for someone who can articulate complex ideas effectively, so practice explaining your work in simple terms.