Senior Robotics Software Engineer

About the role

Dyson is a global technology company that sets out to solve the problems others ignore. We create machines that are different, better and more useful through inventive engineering, relentless testing and a refusal to accept conventional answers. Senior Robotics Software Engineers demonstrate advanced design and problem-solving expertise, leading the development of complex robotics systems and intelligent features. They play a key role in ensuring robustness, scalability, and manufacturability while mentoring junior engineers.

Responsibilities

• Lead design and development of complex robotics behaviours and intelligent features
• Own end-to-end delivery of critical modules or subsystems
• Develop and optimize ML-driven capabilities such as:
• Perception (object detection, mapping)
• Adaptive/autonomous behaviours
• Tackle complex system-level challenges (e.g., latency, reliability, sensor fusion)
• Ensure production-quality code and system robustness
• Provide mentorship and technical guidance to engineers
• Collaborate cross-functionally to align software with product and hardware constraints
• Escalate risks and drive resolution proactively
• AI/ML Responsibilities
• Design and develop end-to-end AI/ML systems for robotics applications, from model selection to deployment
• Own perception and intelligence modules , including:
• Vision-based navigation and mapping
• Sensor fusion (LiDAR, camera, IMU)
• Context-aware and adaptive cleaning behaviours (vacuum robotics focus)
• Optimize and deploy real-time inference on edge devices , including:
• Model compression, quantization, and acceleration
• Performance tuning under embedded constraints
• Lead data-driven development cycles :
• Define data requirements and collection strategies
• Analyze telemetry from deployed robots to improve model performance
• Solve complex AI-related challenges:
• Model robustness in diverse home environments
• Failure detection and recovery strategies
• Guide others in:
• ML model integration best practices
• Experimentation frameworks (A/B testing, offline vs real-world validation)
• Drive adoption of GenAI-assisted workflows :
• Code generation for ML pipelines
• Automated test generation and debugging
• Documentation and knowledge sharing
• About You
• 5+ years in robotics, embedded systems, or related domains (progression from mid-level)
• Advanced proficiency in C++ and Python for building scalable robotics and AI systems
• Strong hands-on experience developing and deploying ML models in production robotics environments
• Deep expertise in robotics perception and intelligence systems :
• Object detection, segmentation, tracking
• Sensor fusion (camera, LiDAR, IMU)
• Navigation (SLAM, localization, motion planning)
• Experience with ML frameworks and deployment tools :
• PyTorch / TensorFlow (training + inference)
• ONNX, TensorRT, or equivalent optimization frameworks
• Proven ability to deploy and optimize edge AI systems :
• Model quantization, pruning, and performance tuning
• Real-time inference under embedded constraints
• Strong experience in data-driven development :
• Dataset definition, labeling strategies, evaluation metrics
• Using real-world telemetry for continuous model improvement
• Solid domain knowledge in vacuum robotics / consumer robotics , including:
• Coverage optimization and navigation efficiency
• Dirt detection and adaptive cleaning behaviours
• Failure handling and recovery strategies
• Demonstrated ability to solve complex AI/system-level problems independently
• Experience mentoring engineers on:
• ML integration and system design best practices
• Experimentation methodologies (A/B testing, simulation vs real-world validation)
• High proficiency with GenAI-assisted development workflows :
• Accelerating ML pipeline development
• Automating testing, debugging, and documentation
• Strong architectural and design skills
• Strong communication and stakeholder management skills

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