Engineering Manager (Computer Vision)

Join Protex as an Engineering Manager (Computer Vision) and lead the Computer Vision Features team in building cutting-edge computer vision applications for edge devices. This hands-on management role requires a strong background in computer vision, deep learning, and software engineering, as well as experience in people management. You will set the technical direction for computer vision at Protex, ship code with the team, and shape the work before it's built. Enjoy a range of benefits, including unlimited holidays, health insurance, and remote working opportunities.

• Lead and manage a multidisciplinary team of computer vision, video, and edge engineers, ensuring accountability and cross-skilling.
• Set the technical direction for computer vision at Protex, following the latest advancements and balancing them with real-world constraints.
• Design, write, and review code, setting standards for testing and reproducibility, and owning delivery from idea to deployment.

• BSc in Computer Science, Engineering, or a related technical discipline
• You're a good communicator with product sense: you connect model quality to client outcomes, write clear design docs, and turn strategic goals into concrete engineering plans
• Hands-on experience with deep learning for computer vision: you've trained and deployed optimised CNN models (e.g. PyTorch, TensorRT, ONNX) and experimented with vision-language models
• Strong opinions on the direction of computer vision, and a track record of setting technical direction, leading architecture discussions and delivering complex technical projects across teams on time, from design to production
• 3+ years of people management within engineering
• Strong Python skills, and experience building data, training or deployment pipelines on cloud infrastructure (AWS preferred), with containers and infrastructure as code
• 5+ years of software or ML engineering experience, including hands-on work on computer vision systems in production, and 2+ years leading or managing engineering teams
• Experience with real-time video analytics or edge deployment (e.g. NVIDIA DeepStream, GStreamer, C++, CUDA)
• Experience with dataset curation or annotation workflows
• Experience running model inference in the cloud (e.g. AWS SageMaker or Bedrock)