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Dyson

Global home appliances and electronics producer

Lead Robotics Software Engineer

Robotics & Autonomous SystemsConfirmed live in the last 24 hours
Full-timeShenzhen, Guangdong Province, ChinaNo salary listedIn-person

About the Job

Requirements

  • At least 8 years of experience in robotics software, artificial intelligence, or embedded systems, with leadership experience.
  • Expert proficiency in C++ and Python, with strong architectural design capability for artificial-intelligence-driven robotics systems.
  • Extensive experience delivering end-to-end artificial intelligence and machine-learning systems at production scale, from data to deployment.
  • Deep expertise in robot autonomy stacks and artificial-intelligence systems, including multimodal perception using vision and LiDAR fusion, simultaneous localization and mapping (SLAM), mapping, semantic scene understanding, autonomous decision-making, and behavioural intelligence.
  • Strong knowledge of advanced artificial-intelligence techniques, including reinforcement learning, adaptive systems, self-supervised learning, and foundation models applied to robotics.
  • Proven experience scaling machine-learning platforms and pipelines, including data collection, labeling and governance; training, validation and evaluation frameworks; and machine-learning continuous integration and delivery pipelines and over-the-air deployment.
  • Advanced expertise in edge artificial-intelligence system optimization, including hardware-aware model tuning for CPU, GPU and NPU, and system-level trade-offs among latency, accuracy and power consumption.
  • Strong domain expertise in vacuum robotics or autonomous consumer products, including intelligent cleaning behaviours, personalization and robust operation across diverse real-world environments.
  • Demonstrated ability to define artificial-intelligence and machine-learning technical strategy and roadmaps.
  • Recognized subject matter expertise in robotics artificial intelligence and machine learning, with influence across teams.
  • Proven leadership mentoring senior engineers and technical leaders.
  • Advanced experience leveraging and scaling generative artificial-intelligence tools across teams, establishing best practices for Copilot and Anthropic usage, and driving measurable improvements in engineering productivity and quality.
  • Ability to evaluate and operationalize emerging artificial-intelligence technologies into product advantage.
  • Demonstrated leadership in setting technical direction, mentorship and capability building.
  • Strong track record of delivering complex systems to production.
  • Strong communication and stakeholder-management skills.

Responsibilities

  • Lead the design and architecture of advanced robotics and artificial-intelligence-driven systems.
  • Drive development of autonomous navigation and behaviour, perception and scene understanding, and intelligent decision-making systems.
  • Support the technical roadmap for robotics features in collaboration with product and architecture teams.
  • Lead algorithm development, evaluation and optimization.
  • Identify technical risks and define mitigation strategies.
  • Act as a subject matter expert and set technical standards.
  • Mentor senior and junior engineers and elevate team capability.
  • Drive experimentation, prototyping and innovation initiatives.
  • Influence cross-team decisions and ensure alignment with product strategy.
  • Define and lead the artificial-intelligence and machine-learning strategy for robotics platforms, particularly intelligent vacuum systems.
  • Architect scalable artificial-intelligence systems, including multimodal perception stacks using vision and LiDAR, autonomous decision-making and behavioural intelligence, and continuous learning systems integrating on-device and cloud capabilities.
  • Drive innovation in advanced perception, including semantic mapping and object understanding; reinforcement learning and adaptive behaviour systems; and predictive and personalized cleaning intelligence.
  • Lead the end-to-end machine-learning lifecycle at scale, including data strategy, training infrastructure and evaluation frameworks, and machine-learning continuous integration and delivery pipelines and over-the-air updates.
  • Establish engineering standards and best practices for machine-learning system reliability, safety and explainability, and edge artificial-intelligence deployment and monitoring.
  • Evaluate and introduce emerging artificial-intelligence technologies, including foundation models applied to robotics and vision-language models for contextual understanding.
  • Review and approve critical machine-learning and artificial-intelligence design decisions, and mentor senior engineers in artificial-intelligence system design.
  • Drive organization-wide productivity through generative-artificial-intelligence enablement, standardize the use of tools such as Copilot and Anthropic across teams, define safe and effective usage practices, and improve engineering velocity, code quality and innovation throughput.

About the Company

Dyson

Global home appliances and electronics producer

Dyson designs and manufactures a range of home appliances, including vacuum cleaners, air purifiers, hair care products, and hand dryers, for consumers and businesses worldwide. Its products rely on high-performance engineering and advanced technology to deliver effective cleaning, air quality, grooming, and hand-drying experiences. Dyson sells directly through its website and via retail partners, earning revenue from product sales and after-sales services. The company differentiates itself through a strong emphasis on research and development to improve performance, introduce new features, and optimize efficiency and usability. Its goal is to keep its products at the leading edge of consumer electronics and home appliances by combining practical design with rigorous engineering.

Company size
10,001+
Company stage
Not listed
Total funding
Not listed
Headquarters
one-north, Singapore
Founded
1991

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