Graduate Research Scientist, AI

Overview

At Arm, our research shapes the future of energy-efficient AI. We build the foundations of tomorrow’s intelligent systems - from next-generation processors and accelerators to cutting-edge ML models and tools. As a Research Scientist, you’ll be part of a global team pushing the boundaries of what’s possible at the intersection of AI, architecture, and scalable compute.

We’re looking for curious, collaborative researchers who want to turn deep technical insights into real-world impact. Whether you’re advancing algorithms for efficient learning, designing ML-friendly compute architectures, or experimenting with new model deployment paradigms - your work at Arm can influence billions of devices worldwide.

• Scalable and Distributed Machine Learning: Approaches for training, inference, and deployment of increasingly capable models across diverse and distributed compute environments.
• Efficient and Sustainable AI: Techniques to improve the performance, efficiency, and scalability of machine learning workloads, spanning algorithms, representations, and system-level optimizations.
• Generative Modeling: Research into modern generative methods for learning, representation, and synthesis across different data types and tasks.
• Multimodal and Integrated Learning: Models and systems that combine multiple sources of information to enable richer perception, understanding, and interaction.
• Autonomous and Adaptive Systems: Learning-based methods for reasoning, decision-making, coordination, and adaptation in complex or dynamic environments.
• Embodied and Interactive Intelligence: Machine learning approaches for perception, planning, and control in systems that interact with the physical world or with users.

Hold (or are on track to hold) a PhD in Computer Science, Electrical/Computer Engineering or related field by spring 2026. Candidates with alternative degrees will also be considered if they have relevant experience.

• Proficiency in programming languages such as Python, C/C++, or similar
• Experience designing, training, or analyzing machine learning models or systems using standard frameworks (e.g. PyTorch, Hugging Face Transforms, etc.)
• Interest in research and long-term innovation beyond immediate product delivery
• Contributions to open-source and/or peer-reviewed publications
• Up to date understanding of machine learning trends
• Familiarity with machine learning model optimization or deployment
• Familiarity with Arm architecture
• Familiarity with GPU programming

In addition to a competitive salary and a comprehensive rewards package, you'll also receive the support, autonomy and opportunity to excel in your career.

With a mid-year, and year-end review you'll have two windows each year to progress recognizing the pace at which you could grow. Attend our Grad-teach-Grads workshops, guest speaker series and various social events to expand your knowledge. Want to take this a step further? Join our Graduate Committee and home in on your planning, networking and co-ordination skills.

You'll also be invited to our exclusive Global Graduate Conference (GGC)! A yearly occurrence exclusive for Graduates allowing you to hear from executive members, inspiring speakers and make connections for life.

With many of our leaders and technical specialists having originally joined as a Graduate, will you be next?

At Arm, we believe progress happens when people are empowered to think bigger and push beyond what seems possible. Our 10x mindset is about curiosity, ambition and creating impact that will be used by millions. We learn fast, prioritise collaboration and turn bold ideas into real technology. We look for people who are inspired by this way of working and want to grow in an environment where bold ideas are welcomed.

Read more about how we bring the 10x mindset to life on the Arm blog.

$165,000-$223,200 per year

Salary is only one component of Arm's offering. The total reward package will be shared with candidates during the recruitment and selection process.

If you need an adjustment or an…