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Dyson

Senior Robotics Software Engineer

Reposted 12 Days Ago
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In-Office
Headquarters, AZ
Senior level
In-Office
Headquarters, AZ
Senior level
Lead design and delivery of robotics software and ML-driven perception/intelligence modules for vacuum/consumer robots. Develop real-time edge inference, sensor fusion, navigation (SLAM), model optimization, and data-driven improvement pipelines. Ensure production-quality code, system robustness, mentor engineers, and collaborate across hardware and product teams.
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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.

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