The posting
About Us
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.
About the Role
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.
Key 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
