At a Glance
- Tasks: Develop AI algorithms for image segmentation and object recognition.
- Company: Join a visionary team transforming stock imagery with AI-driven technology.
- Benefits: Enjoy flexible remote work options and potential equity share.
- Why this job: Shape the future of imagery while collaborating with experienced tech leaders.
- Qualifications: 8+ years in Computer Vision, strong Python skills, and deep learning experience required.
- Other info: Opportunity to join as a contractor or explore long-term roles.
The predicted salary is between 48000 - 84000 £ per year.
📢 Hiring: Computer Vision Engineer (Expert) – AI-Powered Innovation in Stock Imagery
🚀 About Us
We’re building an AI-driven platform that will transform how people interact with stock imagery. Our vision is to create a tool that allows users to seamlessly edit and customise images, without the need for complex software.
To make this a reality, we’re looking for a Computer Vision Engineer (Expert level) to help develop the cutting-edge AI technology behind our platform. You’ll be working alongside a highly experienced CEO and CTO, both with 20 years in world-leading tech companies, shaping a product that redefines the future of imagery.
🔍 The Role
We need an expert in computer vision and deep learning to develop AI-powered image segmentation, object manipulation, and generative models. Your work will be instrumental in delivering a seamless, intuitive editing experience for users.
💡 What You’ll Do
✅ Develop and optimise computer vision algorithms for image segmentation and object recognition.
✅ Work with deep learning frameworks (TensorFlow, PyTorch, OpenCV) to build high-performance AI models.
✅ Implement AI solutions that enable users to edit and customise images with ease.
✅ Collaborate with the founders and engineering team to integrate AI into the platform.
✅ Stay ahead of industry advancements to refine and improve our technology.
🎯 What We’re Looking For
✔️ 8+ years of experience in Computer Vision, AI, or Machine Learning.
✔️ Strong proficiency in Python, OpenCV, TensorFlow, PyTorch, or similar frameworks.
✔️ Experience in image segmentation, GANs, or neural rendering techniques.
✔️ Passion for pushing the boundaries of AI-powered creativity.
🌍 Why Join Us?
🚀 Be part of a cutting-edge AI project set to transform the stock imagery industry.
🛠️ Work directly with the CEO & CTO, both with 20 years’ experience in world-class tech.
💰 Flexible engagement – join as a contractor or explore a long-term role with potential equity share.
🌎 Remote-first culture with flexible working arrangements.
⚡ Interested? Let’s talk!
Computer Vision Engineer (Expert) employer: Ediscene
Contact Detail:
Ediscene Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Computer Vision Engineer (Expert)
✨Tip Number 1
Make sure to showcase your expertise in computer vision and deep learning during networking events or meetups. Engaging with professionals in the field can help you learn about potential job openings and get insider information about our company.
✨Tip Number 2
Stay updated on the latest advancements in AI and computer vision technologies. Following relevant blogs, attending webinars, or participating in online courses can give you insights that will impress us during discussions.
✨Tip Number 3
Consider contributing to open-source projects related to computer vision or AI. This not only enhances your skills but also demonstrates your commitment to the field, making you a more attractive candidate for our team.
✨Tip Number 4
Prepare to discuss specific projects where you've implemented image segmentation or generative models. Being able to articulate your hands-on experience will set you apart and show us that you're ready to tackle the challenges we face.
We think you need these skills to ace Computer Vision Engineer (Expert)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your 8+ years of experience in Computer Vision, AI, or Machine Learning. Emphasize your proficiency in Python and frameworks like TensorFlow and PyTorch, as well as any relevant projects you've worked on.
Craft a Compelling Cover Letter: In your cover letter, express your passion for AI-powered creativity and how your skills align with the company's vision. Mention specific experiences related to image segmentation, GANs, or neural rendering techniques that demonstrate your expertise.
Showcase Relevant Projects: If you have worked on projects involving computer vision algorithms or deep learning models, include them in your application. Provide links to your GitHub or portfolio to showcase your work and contributions to the field.
Highlight Collaboration Skills: Since the role involves working closely with the CEO and CTO, emphasize your ability to collaborate effectively within a team. Share examples of past teamwork experiences that led to successful project outcomes.
How to prepare for a job interview at Ediscene
✨Showcase Your Expertise
Be prepared to discuss your 8+ years of experience in computer vision and AI. Highlight specific projects where you've developed algorithms for image segmentation or object recognition, and be ready to explain the challenges you faced and how you overcame them.
✨Demonstrate Technical Proficiency
Familiarize yourself with the deep learning frameworks mentioned in the job description, such as TensorFlow and PyTorch. During the interview, be ready to discuss your experience with these tools and provide examples of how you've used them to build high-performance AI models.
✨Discuss Industry Trends
Stay updated on the latest advancements in computer vision and AI. Be prepared to share your thoughts on emerging technologies and how they could impact the stock imagery industry. This shows your passion for pushing the boundaries of AI-powered creativity.
✨Collaborative Mindset
Since you'll be working closely with the CEO and CTO, emphasize your ability to collaborate effectively with cross-functional teams. Share examples of past collaborations and how you contributed to integrating AI solutions into existing platforms.