Find a job 
Featured Companies 
Featured Universities 
For Companies At a Glance
- Tasks: Build and deploy real-time detection and tracking systems for UAVs in challenging environments.
- Company: Kessari, a pioneering tech company focused on autonomy solutions.
- Benefits: Competitive salary, equity options, and performance bonuses.
- Why this job: Join a team making a real-world impact with cutting-edge technology in drone operations.
- Qualifications: Experience in object detection, model optimisation, and data pipeline management.
- Other info: Fast-paced environment with opportunities for growth and innovation.
The predicted salary is between 72000 - 108000 £ per year.
We build retrofit autonomy modules for existing UAV fleets operating in GPS-denied environments. This is real-world deployment, not research or simulation. Constrained hardware, degraded comms, systems that have to work first time. Kessari is moving from TRL 6 to TRL 8 with active partners. We need someone to own perception through to targeting, end-to-end.
What you’ll do:
- Build and deploy real-time detection and tracking pipelines on edge hardware
- Take models from training through optimisation into field deployment
- Work on low-latency systems running on constrained GPUs (Jetson class)
- Handle messy real-world data (aerial, oblique, thermal, small objects)
- Ship systems that run at 30+ FPS in production
- Work in GPS-denied conditions where localisation and perception must hold up under uncertainty
You’re a fit if you can:
- Train and deploy object detection models (YOLO, RT-DETR or similar)
- Optimise models for real-time edge inference (TensorRT, ONNX or similar)
- Implement multi-object tracking (ByteTrack, BoT-SORT or similar)
- Own the data pipeline (collection, annotation, validation)
- Work across Python and some C++, Linux, Docker
Strong bonus:
- Experience in GPS-denied navigation or perception systems
- Drone or aerial imagery experience
- Thermal or infrared perception
- Visual SLAM or odometry integration
- CUDA or GPU optimisation
- Synthetic data or simulation
What matters:
This is not a research role. You need to ship fast, handle ambiguity, and make systems work in the field.
Comp: €90k – €140k+ depending on level. Equity and performance upside tied to deployments.
DM directly to apply.
Computer Vision Engineer employer: Kessari
Contact Detail:
Kessari 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, especially those working on UAVs or computer vision. LinkedIn is your best mate here—connect, engage, and don’t be shy about asking for insights or advice.
✨Tip Number 2
Show off your skills! If you’ve got projects or contributions that demonstrate your expertise in real-time detection or model optimisation, make sure to highlight them in conversations. A portfolio can speak volumes!
✨Tip Number 3
Prepare for technical chats! Brush up on your knowledge of object detection models and edge hardware. Be ready to discuss how you’d tackle challenges in GPS-denied environments—this will show you’re not just book-smart but also practical.
✨Tip Number 4
Apply through our website! We love seeing candidates who take the initiative. It’s a great way to get noticed and shows you’re genuinely interested in joining our team at Kessari.
We think you need these skills to ace Computer Vision Engineer
Some tips for your application 🫡
Show Your Real-World Experience: Make sure to highlight any hands-on experience you've had with real-time systems, especially in GPS-denied environments. We want to see how you've tackled messy data and made things work in the field, so don’t hold back!
Tailor Your Application: Take a moment to customise your application for this role. Mention specific projects where you've built or deployed detection and tracking pipelines, and how you’ve optimised models for edge hardware. We love seeing that personal touch!
Be Clear and Concise: When writing your application, keep it straightforward and to the point. We appreciate clarity, so avoid jargon unless it’s relevant. Make it easy for us to see your skills and experiences at a glance!
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 the role. Plus, we can’t wait to see what you bring to the table!
How to prepare for a job interview at Kessari
✨Know Your Tech Inside Out
Make sure you’re well-versed in the technologies mentioned in the job description, like YOLO and TensorRT. Be ready to discuss your experience with real-time detection and tracking pipelines, as well as any challenges you've faced while deploying models on edge hardware.
✨Showcase Your Problem-Solving Skills
Prepare examples of how you've tackled messy real-world data or worked under uncertainty. This role is all about shipping fast and making systems work in the field, so highlight your ability to adapt and find solutions in challenging situations.
✨Demonstrate Your Hands-On Experience
Bring up specific projects where you’ve trained and deployed object detection models or optimised them for edge inference. If you have experience with drone or aerial imagery, make sure to mention it, as it’s a strong bonus for this position.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s current projects and future goals, especially regarding their move from TRL 6 to TRL 8. This shows your genuine interest in the role and helps you understand how you can contribute to their success.