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For Companies At a Glance
- Tasks: Design and maintain high-performance SDKs while deploying machine learning models.
- Company: Innovative tech company in Greater London with a focus on AI and machine learning.
- Benefits: Competitive salary, flexible working arrangements, and opportunities for professional growth.
- Why this job: Join a collaborative team and make a real impact in cutting-edge technology solutions.
- Qualifications: Strong C++ and Python skills, plus experience with SNPE/QNN and TensorRT.
- Other info: Exciting hybrid role with a chance to bridge research and production.
The predicted salary is between 36000 - 60000 £ per year.
A technology company in Greater London is seeking a skilled Computer Vision Engineer to bridge machine learning research and production. You will design and maintain high-performance SDKs, deploy machine learning models across hardware, and optimize performance.
Candidates should have a strong understanding of C++ and Python, plus experience with frameworks like SNPE/QNN and TensorRT. This hybrid role offers opportunities to impact technology solutions in a collaborative environment.
Hybrid C++ Computer Vision AI Engineer — SDK & Deployment in London employer: Zebra Technologies
Contact Detail:
Zebra Technologies Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Hybrid C++ Computer Vision AI Engineer — SDK & Deployment in London
✨Tip Number 1
Network like a pro! Reach out to professionals in the tech industry, especially those working with C++ and computer vision. Attend meetups or webinars to connect with potential employers and get your name out there.
✨Tip Number 2
Show off your skills! Create a portfolio showcasing your projects related to machine learning and SDK development. This will give you an edge and demonstrate your hands-on experience to hiring managers.
✨Tip Number 3
Prepare for technical interviews by brushing up on your C++ and Python skills. Practice coding challenges and be ready to discuss your experience with frameworks like SNPE/QNN and TensorRT. We want you to shine!
✨Tip Number 4
Don’t forget to apply through our website! It’s the best way to ensure your application gets noticed. Plus, we love seeing candidates who are proactive about their job search.
We think you need these skills to ace Hybrid C++ Computer Vision AI Engineer — SDK & Deployment in London
Some tips for your application 🫡
Show Off Your Skills: Make sure to highlight your experience with C++ and Python in your application. We want to see how you've used these languages in real projects, especially if you've worked with frameworks like SNPE/QNN or TensorRT.
Tailor Your Application: Don’t just send a generic CV! We love it when candidates tailor their applications to the role. Mention specific projects or experiences that relate to designing SDKs or deploying machine learning models.
Be Clear and Concise: When writing your application, keep it clear and to the point. We appreciate well-structured applications that make it easy for us to see your qualifications and fit for the role.
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 this exciting opportunity in our collaborative environment.
How to prepare for a job interview at Zebra Technologies
✨Know Your Tech Inside Out
Make sure you brush up on your C++ and Python skills before the interview. Be ready to discuss specific projects where you've used these languages, especially in relation to SDKs and machine learning models. The more you can demonstrate your technical expertise, the better!
✨Familiarise Yourself with Relevant Frameworks
Since the job mentions SNPE/QNN and TensorRT, it’s crucial to have a solid understanding of these frameworks. Prepare to explain how you've used them in past projects or how you would approach using them in this role. This shows that you're not just a coder but someone who can apply their knowledge practically.
✨Showcase Your Problem-Solving Skills
Be ready to tackle some technical challenges during the interview. Practice explaining your thought process when solving problems, especially those related to optimising performance in machine learning deployments. This will highlight your analytical skills and ability to think on your feet.
✨Emphasise Collaboration and Communication
This role is in a collaborative environment, so be prepared to discuss how you work with others. Share examples of successful teamwork, especially in tech projects. Highlighting your communication skills will show that you can bridge the gap between research and production effectively.