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- 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 autonomy.
- 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 90000 - 140000 £ 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 in Manchester employer: Kessari
Contact Detail:
Kessari Recruiting Team
StudySmarter Expert Advice 🤫
We think this is how you could land Computer Vision Engineer in Manchester
✨Tip Number 1
Network like a pro! Reach out to folks in the industry, attend meetups, 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 projects, especially those related to real-time detection and tracking. This will give potential employers a taste of what you can do and how you handle messy real-world data.
✨Tip Number 3
Prepare for technical interviews by brushing up on your knowledge of object detection models and optimisation techniques. Practice coding challenges and be ready to discuss your experience with low-latency systems and edge hardware.
✨Tip Number 4
Apply through our website! It’s the best way to ensure your application gets seen. Plus, we love seeing candidates who are proactive and take the initiative to reach out directly.
We think you need these skills to ace Computer Vision Engineer in Manchester
Some tips for your application 🫡
Tailor Your CV: Make sure your CV highlights relevant experience in computer vision and edge hardware. We want to see how your skills align with our needs, so don’t be shy about showcasing your projects and achievements!
Craft a Compelling Cover Letter: Your cover letter is your chance to shine! Tell us why you’re excited about the role and how your background makes you a perfect fit for our team. Keep it concise but impactful – we love a good story!
Showcase Your Technical Skills: Be specific about your technical expertise, especially with tools like YOLO, TensorRT, or Docker. We’re looking for someone who can hit the ground running, so let us know what you’ve worked on that’s relevant to our projects.
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 role. Plus, it shows you’re keen to join our team!
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. Companies want to see that you can think on your feet and adapt to changing conditions, especially in GPS-denied environments.
✨Demonstrate Your Hands-On Experience
Bring along any relevant projects or case studies that highlight your ability to ship systems quickly. Discuss your experience with multi-object tracking and how you’ve optimised models for edge inference, as this will show you can deliver results in a fast-paced environment.
✨Ask Insightful Questions
Prepare thoughtful questions about the company’s current projects and future goals. This shows your genuine interest in the role and helps you understand how you can contribute to their mission of building effective autonomy modules.