Work Placement / Internship

Research Intern - Machine Learning

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Role Overview

Arm is the industry's leading supplier of microprocessor technology providing efficient, low-power chip intelligence making electronic innovations come to life. Through our partners, our designs power everything from coffee machines to the fastest supercomputer in the world. Our technology enriches the lives of over 70% of the world’s population - and we want to hear from anyone that is interested in working with us on the future generations of compute.

"You're surrounded by the best minds"

Recruiter Katie, explains why you should choose to start your career at Arm. To watch the full Gradcracker/Arm webinar click here.

About Arm and Arm Research

Arm plays a key role in our increasingly connected world. Every year, more than 20 billion products featuring Arm technology are shipped. Our engineers design and develop CPUs, graphics processors, sophisticated system technologies, supporting software development tools, and physical libraries.

At Arm Research, we develop new technology that can grow into new business opportunities. We keep Arm up to speed with recent technological developments by pursuing blue-sky research programmes, collaborating with academia, and integrating new technologies into the wider Arm ecosystem. Our research activities cover a wide range of fields from mobile and personal computing to server, cloud, and HPC computing. Our work and our researchers span a diverse range from circuits to theoretical computer science. We all share a passion for learning and creating.

About the machine learning group and our work

Arm’s Machine Learning Research Lab delivers underlying ML technology that enables current and emerging applications across the full ML landscape, from data centres to IoT. Our research provides the building blocks to deliver industry-leading hardware and software solutions to Arm’s partners.

Our Cambridge ML team focusses on Bayesian Deep Learning and Graph Neural Network with research threads investigating Predictive Uncertainty using Probabilistic ML, Out of Distribution detection in safety-critical applications, efficient processing of Point-Clouds and how to train, optimise, and accelerate them. We also conduct research on compiler optimisation for ML workloads (MLIR), self-supervised learning, distributed and adaptive learning, and data for efficient computation. We deliver models, algorithms, library optimization based on computational analysis, network architecture search (NAS) tools, ideas for instruction set architecture (ISA) and accelerator architecture.

We are looking for interns to work with us in key application areas like autonomous driving (ADAS), mobile health, computer vision (CV), object detection and tracking, motion planning, and simultaneous localisation and mapping (SLAM). As a team we are very interested in researching and developing ML techniques that translate into real products and applications; our interns will help us resolve aspects of fundamental ML technology will be relevant to next generation applications.

Job requirements

Education

  • Our interns typically pursue Masters or PhD degrees or post-docs in machine learning or computer science, data science, engineering, or science combined with a strong component of machine learning, but we encourage applications from any field of study if you are motivated and feel your unique skills are relevant to what we do.
  • We will also consider your application if you are pursuing an undergraduate or bachelor's degree and have relevant project or work experience.

Skills and Experience

  • Hands-on experience investigating foundational Machine Learning technology including algorithms, models, training, optimisation
  • Deep understanding of machine learning/deep learning (CNN, RNN, Graph NN, Transformers) concepts
  • Proven track record of research in sophisticated topics of machine learning (e.g., Bayesian inference, Reinforcement Learning, Federated Learning, Continual Learning etc.)
  • Good knowledge of common ML frameworks (TensorFlow, PyTorch, GPflow, Pyro etc.) and strong programming skills
  • Publication at ML / Hardware conferences, such as, NeurIPS, ICML, ICLR, CVPR, ICCV, ICRA, MLSys, ISCA, HPCA, IEEE, Hot Chips will be a plus
  • Understanding of CPU, GPU, and NN accelerator micro-architecture is a plus

Our internships and how to apply

We invite you to apply for an internship if your research interests align with ours and are enthusiastic about the type of work we do. As an Arm Research intern, you will get a first-hand view of how Arm crafts its technology and maintains an ecosystem of more than one thousand partners that have shipped over 170 billion innovative Arm-powered processors. We will work closely with you to develop an internship project that is tailored to your interests. Our internships are three months long with flexible start dates. We offer continuous support, feedback, and development opportunities as well as flexibility to decide how to complete project tasks.

You will work alongside experienced researchers within a specific team and also the wider research group doing real project tasks. We believe in developing talent for the future, so we seek to offer many of our interns a graduate position once they have finished their studies.

Please provide a cover note with your application; include some information about what you are interested in and the kind of projects you would like to work on. If you have a clear idea about the work you want to do, include it in your letter. It is okay not to be 100% sure! Tell us about your studies and what you enjoy, and we will try to find the right fit for you.

Arm Research recognises that diverse and inclusive teams generate exceptional ideas and innovations critical to an outstanding research organisation's success. We do not discriminate because of race, religion, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

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Opportunity Overview

  • Ongoing
  • Multiple vacancies
  • Competitive salary + benefits
  • Masters and above (expected)
  • 3 Months
  • Cambridge
    (Show map)

Disciplines accepted...

  • Computer Science
  • Cyber Security
  • Data Science
  • Hardware
  • IT Architecture
  • Information Technology
  • Naval Architecture
  • Robotics
  • Software
  • Systems
  • Telecommunications
  • Web Development

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