Computer Vision Engineer X 3 | £50,000 - £95,000
We're working with a specialist technology company scaling a high-performance real-time AI platform on this exciting opportunity.
Join a team that is redefining the boundaries of real-time machine learning deployment. We are looking for three hands-on engineers to own the end-to-end model deployment and optimization of advanced computer vision pipelines using PyTorch, TensorRT, and GStreamer in high-stakes production environments.
The Role
- Lead the deployment and optimization of real-time computer vision models, focusing on object detection, tracking, and classification under strict latency constraints.
- Design and refine complex video processing pipelines using frameworks such as FFmpeg and GStreamer to handle multi-stream inputs.
- Optimize inference performance specifically for GPU and Edge AI platforms, leveraging ONNX and TensorRT toolchains for maximum efficiency.
- Collaborate closely with Systems Engineers to bridge the gap between pure ML research and high-performance production code.
- Balance critical trade-offs between model accuracy and inference speed to ensure seamless performance in resource-constrained environments.
What You'll Need
- Expert-level Python skills specifically applied to ML inference workflows and production-grade code development.
- Deep hands-on experience with PyTorch and a solid grounding in computer vision fundamentals like detection, segmentation, and tracking.
- Proven track record of deploying ML models into live production environments, rather than just academic or research-only settings.
- Practical experience with video processing frameworks (GStreamer/FFmpeg) and optimizing for Linux-based development environments.
- Proficiency with optimization tools such as TensorRT or ONNX, and experience with containerized ML deployments (Docker/Kubernetes).
What's On Offer
- Competitive salary range of £50,000 - £95,000 based on experience and technical proficiency.
- The chance to work at the forefront of Edge AI, solving complex debugging challenges on real-world, high-traffic systems.
- A pragmatic, engineering-first culture that values hands-on coding, clear documentation, and real-world results over corporate hierarchy.
Apply via Haystack today!
