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Machine Learning Software Engineer


SGD Competitive Remuneration Package
Robotics, Software Engineering and Connectivity
Singapore - Singapore

About us

Dyson began 30 years ago with James Dyson and a handful of engineers questioning everyday products, thinking differently and making them better. We are now the world's number one vacuum cleaner manufacturer in the UK, US, Japan, Europe and Australasia.

We've even branched out to improving commercial technology that frustrates us. The Dyson Airblade hand dryer dries hands in ten seconds, it’s also the most hygienic and energy efficient hand dryer available. And more recently a fan, Air Multiplier, with no blades or grille.

There are over 4000 in the world and we’re all inventive and hugely passionate about what we do. At our Development Centre in Johor Bahru, Malaysia & Singapore there are almost 1600 of us, a mixture of engineers and support staff, we are Dyson people that are encouraged to think differently, challenge convention and be unafraid to make mistakes. Our teams there will rise to more than 2000 over the next 2 years.

About the role

You'll be an experienced software engineer with high-level machine learning knowledge. Working in an agile cross-functional team, you will contribute to the development of complex features to ensure Dyson continues to create innovative products that will delight our customers.

You'll collaborate with architects, software engineers, machine learning engineers, and platform engineers to help solve the wide and exciting range of edge devices’ challenges posed by the ever expanding Dyson product portfolio.

You'll have a desire to explore and share ideas and techniques across different technical domains and will ideally have expert knowledge of software development for complex, sophisticated systems including deep learning IPU, embedded software, camera/sensors components with a focus on model deployment on embedded system software and cloud computing.

  • Ability to deploy proposed machine learning algorithm/model onto target platform efficiently.
  • Work closely with architects, algorithm engineers, and platform engineers to implement and deploy machine learning models on embedded system and optimize product performance accordingly.
  • Understand necessary data and AI requirements to implement and deploy machine learning applications; ensure machine learning applications are available to products via well-defined APIs
  • Develop prototype demonstrators utilising rapid prototyping techniques for quick evaluation.
  • Manage the entire life cycle of multiple related complex modules and systems, including feature discussion, algorithmic analysis, documentation, design, coding, testing, maintenance, and result tracking
  • Involve in continuous integration and continuous delivery (CI/CD) infrastructure/environment setup
  • Good product sense and keen focus on product performance.
  • Act as subject matter expert (SME) in specific domain, disseminating knowledge, guiding and mentor engineers in methodology, best practice and standards
  • Proactively identify technical risks within projects and influence engineering teams in their resolution
  • In-depth participation in feature design discussions will be required

About you

  • A bachelor's degree or higher in Computer Science, Electronics Engineering, Computer Engineering, Applied Mathematics, or robotics engineering related fieldswith strong quantitative background.
  • Industry experience in building innovative end-to-end machine learning systems is a plus
  • Familiar with at least one area of the computer vision including but not limited to feature tracking, image embedding, image classification, object detection, image segmentation, etc.
  • Experience in building, deploying and optimizing machine learning algorithms, especially deep learning and convolutional neural network is a plus.
  • Proficient in machine learning libraries, such as OpenCV, dlib, scikit-learn, numpy or scipy, etc.
  • Experience in AWS, Google Cloud or Microsoft Azure cloud service is a plus
  • Good command of object oriented programming capability, including speed and overall quality; specifically, must be able to write high performance product quality codes with C++ and Python
  • Familiar with STL, boost C++ libraries, design patterns and able to enforce it in day-to-day tasks.
  • Proficiency in multithreading programming and synchronisation mechanisms.
  • Comfortable and familiar with embedded system programming under Linux environment for machine learning model deployment and performance tuning. 
  • Concept of machine learning fundamentals, such as data visualisation, data cleaning, SVM, deep learning deployment etc.
  • Good problem-solving and troubleshooting attitude with excellent analytics skills
  • The ability to learn continuously and improve oneself.
  • Experience in Agile practices is a plus.
  • Professionalism and excellent communication skills; ability to communicate complex information to both technical and non-technical stakeholders.
  • Optimism and an excitement about collaborating with teammates and interdisciplinary teams, and technically support development.
  • Independent, Integrity and self-driven with a strong focus on results to ensure that the whole team succeeds in its goals.
  • Fluent in spoken and written English.


Dyson Singapore monitors the market to ensure competitive salaries and bonuses. Beyond that, you’ll enjoy a transport allowance and comprehensive medical care and insurance. But financial benefits are just the start of a Dyson career. Professional growth, leadership development and new opportunities abound, driven by regular reviews and dynamic workshops. And with a vibrant culture, the latest devices and a relaxed dress code reflecting our engineering spirit, it’s an exciting team environment geared to fuelling and realising ambition.

Interview guidance

We are following the government guidelines regarding COVID19. At this time all interviews will be conducted via video or telephone. We’re taking these precautionary measures to protect both our employee and candidate wellbeing. Our Talent Acquisition team will work with you and provide further information as appropriate.