Senior Machine Learning Engineer

About us

Advanced robotics will change the world of engineering for good. At Dyson, we have been developing robot technology for over 20 years – 200 engineers, 420 patents and £28m has already gone into our first robot vacuum. But this is just the start of the domestic robotics revolution. The team is advancing the systems that make our robots more intelligent, adaptable, and physically capable.

About the role

The senior machine learning engineer will build and maintain the tools and infrastructure necessary for developing, testing and integrating state-of-the-art machine learning solutions. The role is fundamental in enabling rapid and efficient research. The position will be located within our robotic perception team, but you will have the opportunity to work with the broader robotics research team, including robot learning, control and software integration, as well as collaborating with Dyson's Machine Learning, Connectivity and Cloud Architecture teams: all with the backdrop of a friendly and multicultural environment.  The role will be based at our Hullavington campus embedded within our robotics group.
Our robotics research team works predominantly on early-stage projects and you will have the opportunity to play a formative role in how these technologies are developed. In addition to developing tools and infrastructure, you will contribute to rapid prototyping, training and evaluation of the ML solutions developed by our team.

About you

Accountabilities:

• You will develop and maintain our data collection tools and infrastructure.

• You will manage our ML datasets.

• You will train and evaluate ML models, including designing of training protocols, hyper-parameter tuning and tracking and visualisation of experiment variables.

• You will deploy large ML models on real robots with constrained resources.

• You will establish and monitor performance metrics.

• You will work with the wider robotics research team to allow for seamless and efficient integration of our ML solutions into our broader systems.

What you must have:

• An MSc (or equivalent industrial experience) in machine learning applied to practical perception problems.

• A sound understanding of machine learning theory and best practices.

• Experience in using modern machine learning frameworks (e.g. PyTorch, TensorFlow) 

• Practical experience in prototyping, training and evaluating large ML models.

• A good grasp of the data requirements for building ML models.

Desirable

• A basic understanding of MLOps.

• Experience in developing and deploying software in a Linux environment.

At Dyson, we seek people that can demonstrate initiative, creativity, and the ability to learn fast. As a growing team, working at the forefront of robotics research, we expect all of our candidates to be good communicators and to have the ability to work both autonomously, with limited supervision, as well as collaboratively, in a tightly-coupled, cross-functional and multi-cultural team. 

Benefits

Financial:

• Performance related bonus

• Company paid Life Assurance

• Discounts on Dyson machines

• Competitive pension scheme

• Purchase additional holidays

Lifestyle:

• 27 days holiday plus statutory bank holidays

• Free bus travel to and from Hullavington campus from Bristol, Chippenham and Swindon

• On-site parking

• Endless free coffee and tea, and a free lunch 

• Digital lifestyle Assist

• Electric vehicle scheme 

Health:

• Private Medical insurance for all employees

• Employee Assistance Program for employee and dependents

• Digital GP and prescription service

• Fertility treatment support

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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.