AI Deploy Engineer

Job description

OUR MISSION: At Sunrise Robotics, we are dedicated to augmenting humanity through intelligent robotics. Our mission is to elevate the world of manufacturing by introducing intelligent, flexible robots that enhance human capabilities and existing machinery, ushering in the next era of production at higher quality, with less waste, and lower cost. OUR VISION: We see a future where every element of manufacturing, from design to assembly, is optimised with intelligent automation. Our vision is to integrate flexible robotic solutions, based on generic hardware and advanced software/AI capabilities, into manufacturing, particularly in small and medium-sized enterprises, to make automation economically viable and accessible, for all sizes of manufacturers. We are not just building robots; we are creating the strategically crucial components for autonomous, intelligent agents of the future. THE ROLE: Sunrise Robotics builds automation that runs in real factories, on real production lines. As an AI Delivery Engineer, you are the bridge between development and deployment - the person who takes AI vision and robotics applications and makes them work in production, 24/7, on real hardware at customer sites. You will build and ship applications powered by our internal stack, monitor their performance in the field, and feed what you learn back into improving the platform. Your work has a direct line to deployed robot cells - and your experience in the field will shape how our stack evolves. WHAT YOU'LL DO: - Build and deploy end-to-end AI vision and robotics applications to production on real-world and simulated robotic systems. - Own technical delivery from application design through to deployment and iterative improvement. - Monitor, diagnose, and address issues in deployed AI and robotics applications. - Configure logging, observability, and alerting systems to track application health and behaviour in the field. - Monitor and re-train algorithms in production; perform A/B testing and re-deploy with confidence. - Generate and curate data to improve models and applications over time. - Work closely with engineering and AI teams to integrate components and deliver production-grade solutions. - Support our Forward Deploy Engineering team when technical issues require deeper investigation. WHAT YOU'LL NEED: - A strong background in 2D/3D computer vision and deep learning, with at least 2 years building solutions for production-grade systems. - Strong Python skills and hands-on experience with deep learning frameworks such as PyTorch or TensorFlow, and computer vision frameworks such as OpenCV. - Experience training and deploying AI models, with familiarity with MLOps practices and Docker. - Experience with ROS or ROS2 and familiarity with robotics systems. - Experience with imaging hardware - industrial cameras, 3D cameras, or stereo systems. - The ability to break down complex problems into structured, efficient solutions and communicate them clearly across technical and non-technical teams. - Comfortable working with international, cross-functional teams and happy to travel regularly. WHAT MAKES YOU STAND OUT: - Experience with synthetic data generation, domain transfer, or designing data collection strategies. - Familiarity with AWS or Google Cloud. - Experience with NVIDIA edge devices and their robotics stack. - Experience with ABB robots and their software suite. WHY US: We're building flexible robotic automation that runs in live manufacturing environments across Europe - and this role sits at the intersection of AI research and real-world deployment. - Production, not prototypes: Your applications will power robot cells running continuously at customer sites. The feedback loop between what you build and what happens in the field is short and direct. - Shape the stack: What you learn in the field feeds directly back into how our platform evolves. This isn't a role where deployment is the end of the story. - Cross-functional exposure: You'll work across AI, engineering, and Forward Deploy - with visibility into the full pipeline from model development to customer delivery.