Senior Computer Vision Engineer

deeptech AV start-up are developing multiple platforms capable of navigating through challenging outdoor environments. This is a fast growing team aiming to nearly double in size this year. They already have funding and customers in place with exciting strategic partnerships to announce in the coming months.

They’re building multi-modal systems that integrate vision, LiDAR, radar, thermal, and language models into real-time AI for autonomous platforms.

This is deeply applied work, where advanced research is translated into operational capability. The expectation for Senior Engineers and Technical Leaders joining the business is impact, if you believe you can lead and add value they will not stifle you and provide an environment for you to thrive and see your ambitious ideas implemented into physical products.

They are seeking technical specialists across several domains including:

• Computer vision & multi-sensor fusion
• Robotics & embedded AI
• Vision-language models & real-time decision-making
• Edge systems deployment

This client is open to candidates at all levels of seniority across the above domains. If you’re more senior than the listed role, we still encourage you to apply.

Key Responsibilities

• Design and implement cutting-edge computer vision and sensor fusion algorithms across modalities (e.g., visual, thermal, radar, LiDAR).
• Develop AI models suitable for edge and embedded platforms (e.g., Nvidia Jetson, Raspberry Pi).
• Collaborate with engineers, researchers, and domain experts to integrate perception modules into operational systems.
• Build and maintain robust ML pipelines suitable for constrained or offline environments.
• Stay current with developments in vision-language models, generative AI, and multi-modal learning, and apply relevant advances to ongoing work.

Your Experience

• Demonstrable experience deploying solutions into defence, aerospace, or other regulated domains.
• Deep understanding of computer vision techniques for detection and localisation.
• Strong experience working with embedded or constrained compute platforms.
• Proficiency in Python and major machine learning frameworks (e.g., PyTorch, TensorFlow).
• Experience with version control (Git), containerisation (Docker), and cloud technologies (e.g., AWS).
• Experience with building and maintaining end-to-end ML pipelines.

Nice-t0-haves

• Experience in start-up or rapid R&D environment
• Familiarity with MLOps and best practices in ML system reliability.
• Experience designing and deploying RESTful APIs.
• Contributions to open-source projects, GitHub portfolio or published research.
• Experience engaging stakeholders, writing technical documentation or supporting proposals.

Apply today for immediate consideration. For information about this and other roles within AI, feel free to reach out directly.