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- Tasks: Develop and optimise cutting-edge computer vision models in the YOLO ecosystem.
- Company: Leading AI technology firm based in London with a focus on innovation.
- Benefits: Competitive salary, hybrid work model, generous vacation, and advanced tech.
- Why this job: Make significant contributions to AI and work with state-of-the-art technology.
- Qualifications: Extensive experience in computer vision, deep learning, Python, and PyTorch.
- Other info: Join a high-performance team with exciting growth opportunities.
The predicted salary is between 48000 - 72000 £ per year.
A leading AI technology firm is seeking a Computer Vision Engineer in London. This role involves developing and optimizing state-of-the-art computer vision models, particularly in the YOLO ecosystem. Candidates should have extensive experience in computer vision and deep learning, with proficiency in Python and PyTorch. The company values high performance and offers a competitive salary, hybrid work model, generous vacation, and advanced tech. If you’re ready to make significant contributions to AI, this opportunity is for you.
Senior Computer Vision Engineer - YOLO & ML Ops (Hybrid UK) employer: Ultralytics
Contact Detail:
Ultralytics Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Senior Computer Vision Engineer - YOLO & ML Ops (Hybrid UK)
✨Tip Number 1
Network like a pro! Reach out to folks in the AI and computer vision space on LinkedIn. Join relevant groups, attend meetups, and don’t be shy about asking for informational chats. 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 in computer vision and deep learning. 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 your Python and PyTorch skills, and be ready to discuss your experience with YOLO models. Practise common technical questions and even some behavioural ones to show you’re not just a coding whiz but also a great team player.
✨Tip Number 4
Don’t forget to apply through our website! We’ve got loads of opportunities waiting for talented individuals like you. Plus, applying directly can sometimes give you a better chance of getting noticed by hiring managers.
We think you need these skills to ace Senior Computer Vision Engineer - YOLO & ML Ops (Hybrid UK)
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights your experience with computer vision and deep learning. We want to see your skills in Python and PyTorch shine through, so don’t hold back on showcasing relevant projects!
Craft a Compelling Cover Letter: Your cover letter is your chance to tell us why you’re the perfect fit for this role. Share your passion for AI and how your background aligns with our needs in the YOLO ecosystem. Keep it engaging and personal!
Showcase Your Projects: If you've worked on any cool computer vision projects, make sure to mention them! We love seeing practical applications of your skills, especially if they involve state-of-the-art models or innovative solutions.
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 don’t miss out on any important updates from our team!
How to prepare for a job interview at Ultralytics
✨Know Your YOLO
Make sure you brush up on the YOLO (You Only Look Once) architecture and its various versions. Be prepared to discuss how you've implemented or optimised YOLO models in your previous work. This shows that you’re not just familiar with the theory but have practical experience too.
✨Showcase Your Python Skills
Since proficiency in Python is a must, be ready to demonstrate your coding skills. You might be asked to solve a problem on the spot, so practice common algorithms and data structures. Having a few snippets of code ready to share can also help illustrate your expertise.
✨Deep Dive into Deep Learning
Prepare to discuss deep learning concepts in detail. Be ready to explain how different architectures work, particularly in relation to computer vision. Use examples from your past projects to highlight your understanding and experience in this area.
✨Ask Insightful Questions
Interviews are a two-way street! Prepare thoughtful questions about the company's projects, team dynamics, and future goals in AI. This not only shows your interest but also helps you gauge if the company is the right fit for you.
