Level

Dyson

Robotics Software Engineer

Dyson is hiring a Robotics Software Engineer in Singapore, Singapore. Level rates it ; you can apply on Dyson.

Level's read on this job

  • On Level's scale, this software engineer role is Builds AI ●●●●: the job is building AI systems.
  • Tools and skills the posting cites include PyTorch, scikit-learn and computer vision.
  • Level classifies it as a junior role.
  • Level lists 486 other open roles at Dyson.
  • The role was posted in the last few days.

AI in this role

pytorchscikit-learn
computer-vision
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, rigorous testing and a commitment to exploring new possibilities.

At Dyson, we believe that diverse experiences, perspectives and ways of thinking help us create better products for our users. We encourage applications from candidates of all backgrounds and are committed to

creating an inclusive environment where everyone can thrive and contribute.


About the role

You are a software engineer with 1–2 years of relevant industry experience in machine learning, computer vision, or software development, working within an agile, cross-functional team. You will apply your practical engineering experience to develop intelligent features that help Dyson deliver innovative products for our customers.


Working collaboratively with machine learning specialists, data operations, UX/UI designers, and software engineers across embedded, cloud, and app teams, you will take ownership of well-defined engineering tasks and contribute practical solutions to Dyson’s expanding portfolio of intelligent products.


You will have practical software development experience and working knowledge of sensors and systems, such as embedded software, cameras, sensor components, or machine learning accelerators. Experience processing data across embedded, app, or cloud environments and delivering software within a professional engineering team would be beneficial.


Key Responsibilities:

  • Design, develop, test, and deploy well-defined machine learning, computer vision, or data-driven features across embedded, cloud, and app platforms
  • Work with machine learning specialists, data operations teams, UX/UI designers, and software engineers to solve engineering problems and deliver agreed outcomes
  • Develop and maintain data pipelines and workflows for collecting, processing, and using sensor data
  • Analyze user and device data to support feature development and improve models or algorithms
  • Integrate model outputs into user-facing interfaces in collaboration with UX/UI and application teams
  • Contribute to proof-of-concept activities, including data collection, annotation, feature bring-up, and evaluation
  • Deploy models and evaluate performance across hardware and software platforms, particularly edge devices
  • Develop and use well-defined APIs and interfaces for machine learning and data-driven features
  • Identify and raise technical risks, blockers, and quality concerns promptly, working with experienced engineers on complex issues
  • Build prototype demonstrators and carry out structured evaluations of new ideas
  • Contribute to the maintenance and improvement of CI/CD infrastructure for model and software delivery
  • Participate actively in code reviews, technical discussions, documentation, and knowledge-sharing activities
  • Maintain a strong focus on product quality, performance, user experience, and reliable feature delivery

About you

Key Skills / Experience

  • A bachelor’s degree in Computer Science, Electronics Engineering, Computer Engineering, Applied Mathematics, or a related discipline with a strong quantitative foundation
  • Working knowledge of image classification, segmentation, embeddings, or feature extraction
  • 1–2 years of relevant industry experience in computer vision, machine learning, data science, or software development
  • Practical experience with the machine learning development lifecycle, including data preparation, model training, evaluation, and deployment
  • Practical knowledge of machine learning fundamentals such as data visualisation, data cleaning, classical machine learning methods, and deep learning
  • Hands-on experience deploying or integrating computer vision or machine learning applications on embedded systems or edge devices is desirable
  • Experience using libraries and tools such as OpenCV, scikit-learn, NumPy, SciPy, or PyTorch
  • Object-oriented programming skills and the ability to write clear, maintainable, and testable code in C++ or Python; experience with both is an advantage
  • Experience working in Linux development environments; exposure to embedded programming, model deployment, debugging, or performance analysis is desirable
  • Exposure to AWS, Google Cloud, or Microsoft Azure in a professional or project environment is a plus
  • A logical and structured approach to problem-solving, debugging, and troubleshooting, with the ability to work independently on well-defined tasks
  • Good communication skills and the ability to explain technical information clearly to colleagues from different disciplines
  • Demonstrated ability to collaborate effectively within software and interdisciplinary engineering teams
  • A growth mindset, openness to feedback, and willingness to develop deeper technical expertise
  • Self-motivated, responsible, and committed to delivering high-quality work as part of a team
  • Fluent in spoken and written English


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.

How we rate this

Robotics Software Engineer at Dyson rates 84 out of 100 for how much of the daily work is AI. That makes it Builds AI (AI Level 4 of 4). The level is about AI in the job, not seniority.

Classification

Builds AI. The job is building AI systems.

  1. ●●●● Builds AI80 to 100
  2. ●●●○ Works on AI60 to 79
  3. ●●○○ Uses AI40 to 59
  4. ●○○○ Little AI0 to 39

Levels come from how often the tools, models and workflows of the role are named in the posting itself. Read the description and count the AI tools, models and workflows it names.

Prepare for this job

Built from this posting and from similar jobs on Level.

Skills and AI tools this role asks for

Computer visionPyTorchscikit-learn

Also common in software engineer jobs at this level

Pay

Typical software engineer job
$168k

This posting doesn't list pay. Use the typical software engineer figure when pay comes up. See software engineer jobs

Questions you could be asked

  1. Walk me through a computer vision problem you solved, from raw data to a deployed model.
  2. Walk me through how you've used PyTorch in your day-to-day work.
  3. What are the limits of scikit-learn that you've run into, and how did you work around them?
  4. How would you decide a model or AI system is ready to ship?
  5. Tell me about a time a model underperformed in production. How did you find out, and what did you change?

Adapt your resume

  • List these exact terms on your resume: Computer vision, PyTorch, and scikit-learn. An applicant tracking system matches the wording, not the idea.
  • Attach one line of real, concrete experience to at least one of them. A tool named with nothing behind it rarely survives a human read.
  • Lead with what you built, trained or shipped. This role is judged on the AI system itself, not the tools around it.

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