This role presents a fantastic opportunity to move into Machine Learning and Artificial Intelligence, key technologies for the future of computing. Working on the cutting edge of Arm IP, you will be creating technology that powers the next generation of mobile apps, portable devices, home automation, smart cities, self-driving cars, and much more.
About the role
Arm is entering a new growth phase to develop innovative technologies and products for existing and new markets. To do this we need talented and motivated people to join our global team. At Arm you will work with the world’s best companies as they build sector-leading products from our designs. You’ll share ideas with and learn new skills from the best engineers in the world. We work in small teams, so your contributions will make a difference. This role offers you the opportunity to lead, challenge the status quo and ultimately change the world of machine learning and artificial intelligence.
As a ML Software Graduate, you will participate in an advanced research and development of the new technology for machine learning. You are assumed to have some experience in SW development, preferably in technology related to machine learning, Signal processing, Control software. You also have a strong ability to communicate your work both orally and in text and will take an active part in working together with both hardware and system test engineers.
What will I be accountable for?
You will be joining a multinational and dynamic Machine learning development group located across Cambridge (UK), San-Jose (US), Galway (IR) and Lund (SE). The team in Lund is responsible for machine learning hardware and software IP.
You will work/attend developing/design/architect new features and evaluate their performance. The features are mainly in the field of machine learning, signal processing software, test frameworks, test automation but also on system level software like RTOS, memory handling, Ethernet, UART, debug protocols and more.
For a sneak peak what it’s like to work in ARM Lund, please have a look at the following video: http://bit.ly/2kxWMXp