Robotics Software Engineer

Dyson Institute; Singapore; On-site; SGD 90,000 - 135,000; Full time

Job summary

Dyson Institute seeks a software engineer with 1–2 years of experience in machine learning, computer vision, or software development to join a cross-functional team.

You will work with embedded, cloud, and app platforms, applying practical engineering to deliver intelligent features for Dyson products. Strong Python/C++ skills and Linux experience are expected.

Qualifications

• Bachelor's degree in Computer Science, Electronics/Engineering or related field with strong quantitative basis.
• 1–2 years of industry experience in ML, CV, data science, or software development.
• Hands-on experience deploying ML/CV on embedded systems or edge devices is a plus.

Responsibilities

• Design, develop, test, and deploy machine learning or data-driven features across embedded, cloud, and app platforms.
• Collaborate with ML specialists, data ops, UX/UI, and software engineers to deliver outcomes.
• Develop data pipelines for collecting, processing, and using sensor data.
• Evaluate model outputs and improve performance across hardware and software platforms.

Skills

Machine learning

Computer vision

Python

C++

Linux

OpenCV

PyTorch

Education

Bachelor's degree in Computer Science/Engineering

Quantitative/math foundation

Tools

TensorFlow

Docker

Job description

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
• Deploy 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. At Dyson we are focused on solving the problems that others have ignored; solving them first using our technology and ingenuity. In order to achieve this we need to pioneer technologies that are different and authentic. This is the core of what we do and who we are. We must strive to create the future, every single day by developing new things, different things, things that go against the grain with a diverse and global team of ingenious minds. Dyson employs 14,000 people and is present in more than 80 countries. And while we are growing fast we want Dyson to remain a start‑up in spirit with the freedom of experimentation and learning, constantly reinventing our products as well as reinventing how we work, how we sell and how we support our owners. At the same time we are working through the James Dyson Foundation, James Dyson Award and Dyson Institute to inspire future engineers and pioneering a new approach to engineering education. Underlining everything we do in this diverse environment is the need to always show respect, supporting each other as one team to overcome whatever challenges we encounter. We drive empowerment, development and equality in an inclusive environment for our people around the world. The future doesn’t just happen, we look to make it happen, to achieve leaps through pioneering new ideas.