Senior Robotics Software Engineer
Summary
Lead the design and development of AI-driven robotics systems for Dyson’s vacuum robots, focusing on perception, sensor fusion, and adaptive cleaning behaviors using C++/Python and ML frameworks.
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
Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity.
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
Dyson is an equal opportunity employer. We know that great minds don’t think alike, and it takes all kinds of minds to make our technology so unique. We welcome applications from all backgrounds and employment decisions are made without regard to race, colour, religion, national or ethnic origin, sex, sexual orientation, gender identity or expression, age, disability, protected veteran status or other any other dimension of diversity.