You will work with JavaScript, TypeScript, and offensive security tools for penetration testing, reverse engineering, and vulnerability assessments. You join a specialist security team at a global leader in Computer Vision, AI, and biometric identity, acting as the bridge between Security and Engineering to embed security throughout web application development.

You’ll train, debug and improve computer vision and 3D perception deep‑learning models using LiDAR, multi‑view geometry, tracking and 3D reconstruction. You’ll build scalable data pipelines with auto‑labelling to deliver ADAS perception capabilities (detection, segmentation) for real‑world driver assistance.

You will work with Python, PyTorch, and geometric deep learning methods (e.g., NeRF, SLAM, VIO, feature matching) to build scene matching, geo-registration, and 3D reconstruction systems for defence AI. The team specialises in scene understanding and localisation, delivering AI capabilities for machine perception and human decision-making under real-world hardware and adversarial constraints.

Axon★3.3 (126)· London

You will work with Python/C++, PyTorch, TensorFlow, AWS, AzureML, and edge hardware (Qualcomm, NVIDIA, Intel) using TensorRT, ONNX, and SNPE. As part of Axon’s CoreAI team, you will drive end-to-end development of AI systems across cloud, edge, and robotics platforms, building production systems for computer vision, NLU, multimodal AI, and GenAI.

Axon★3.3 (126)· London

Work with LLMs, MLLMs, Computer Vision, and GenAI using Python, C/C++, TensorFlow, PyTorch, or Keras and ROS. As part of Axon's AI team, advance state-of-the-art models for intelligent reasoning and perception of multimodal data, deploying them in cloud, devices, and robotics. Provide technical leadership to junior scientists.

You'll work with AWS, Kubernetes (EKS), Terraform/Pulumi, Docker, Python/Go, and edge/IoT infrastructure tools to build and maintain Coram AI's cloud-native video security platform, which uses computer vision and AI for real-time alerts and multi-site visibility. Responsibilities include provisioning AWS resources, managing large IoT device fleets, building CI/CD pipelines, and maintaining observability and compliance across edge and cloud systems.

You'll develop world models, foundation models, and reinforcement learning systems using Python and PyTorch, focusing on areas like diffusion-based generative modeling, spatial AI, and multimodal learning. Wayve builds embodied AI software and foundation models that enable autonomous vehicles to perceive and navigate complex environments without maps. The role requires 3+ years deploying ML systems in production, a PhD or Master's in ML/Computer Vision/Robotics, and publications at top-tier conferences.

You will develop computer vision models for object recognition, tracking, video understanding, and scene matching using deep learning architectures and state-of-the-art methods, optimizing them for hardware constraints and adversarial robustness. The role involves designing experiments, benchmarking performance in real-world scenarios, and collaborating across teams at Helsing, a defence AI company building AI-based capabilities for democratic protection. You should have an MSc in computer science, machine learning, or robotics with strong Python software engineering skills and experience deploying AI systems to production.

You'll build and own an internal web application using React, TypeScript, and established backend frameworks, integrating with Databricks-backed workflows and internal APIs to help teams browse computer vision models and explore results. As the first dedicated fullstack hire in the Corpus & Enrichment team at Wayve—a developer of embodied AI for autonomous driving—you'll partner directly with internal stakeholders to ship an MVP quickly and iterate based on feedback.