Graduate ML Hardware Modelling Engineer
ArmJob Title
Graduate ML Hardware Modelling Engineer
Role Summary
Join the NPU hardware modelling team to develop and validate ML hardware models used across design, verification and compiler workflows. You will implement features, measure performance, and maintain models used in customer engagements.
Work closely with ML hardware design, verification and compiler teams to deliver well-tested code, debug integration issues, and support the product architecture and specification.
Experience Level
Entry-level / Graduate program. Suitable for recent graduates or candidates finishing a Bachelor’s, Master’s or PhD; typically 0–2 years of professional experience.
Responsibilities
Deliver software and models that represent ML hardware, collaborate across teams, and help ensure the hardware runs efficiently in customer and internal flows.
- Design, implement and test new features on the ML hardware modelling platform.
- Measure and report model performance; optimise where required.
- Collaborate with hardware design and verification teams to debug and resolve integration issues.
- Support the compiler team to ensure efficient hardware execution and correct mapping of workloads.
- Maintain model code and documentation as an external deliverable for customer engagements.
- Write well-tested, maintainable code and follow team software processes.
Requirements
Concise list of must-have and nice-to-have skills. Degree requirements are listed separately under Education Requirements.
- Must-have: Strong programming skills (preferably C or C++), strong analytical/problem-solving ability, and experience or comfort working in a fast-paced engineering environment.
- Must-have: Ability to collaborate with hardware design, verification and compiler teams and to deliver tested, production-quality code.
- Nice-to-have: Experience with source control workflows (Git, Gerrit, Repo).
- Nice-to-have: Understanding of SystemC, HLS flows, or hardware modelling/build processes.
- Nice-to-have: Familiarity with agile software development, machine learning frameworks, or signal processing concepts.
Education Requirements
Hold, or be on track to hold by programme start, a Bachelor's, Master’s or PhD in Machine Learning, Electrical Engineering, Engineering Physics, Computer Science, or a similar technical field. Applicants should be prepared to provide an academic transcript when requested.
About the Company
Company: Arm
Headquarters: Cambridge, United Kingdom
ARM is a global leader in semiconductor and software design, driving innovation in computing technology. The company specializes in designing processors and systems that provide the essential building blocks for electronic devices. ARM's architecture is widely used in smartphones, servers, and IoT devices, and its collaborative culture fosters bold thinking, diversity, and high-impact benefits for its talented workforce.
