Experienced Machine Learning Framework/Runtime Software Engineer

Experienced Machine Learning Framework/Runtime Software Engineer

Specific Skills and Experience Required
We’re looking for strong C++ software development experience, ideally gained while building machine learning inference engines, runtime systems, or backend integration frameworks. Experience working with a machine learning inference framework such as LiteRT, TensorFlow Lite, ONNX Runtime, or a similar technology is also important.

A good understanding of how AI models execute in practice is essential, including graph processing, operator execution, memory management, and backend integration. This role involves analysing, investigating, diagnosing, and resolving complex functional or performance issues across frameworks, runtimes, compilers, drivers, and hardware abstraction layers.

The work brings together engineers across runtime, compiler, driver, and hardware teams to design, develop, integrate, test, and optimise solutions within a large, modular codebase. Strong analytical and problem-solving skills, combined with an interest in machine learning systems, AI acceleration, and performance optimisation, will support success in the role.
Beneficial but Not Required
Experience across every area below is not expected. Relevant knowledge or experience could include:

• Developing delegates, execution providers, plugins, or other backend integration mechanisms
• GPU programming or machine learning acceleration technologies such as Vulkan, OpenCL, TOSA, or compute kernels
• Designing or implementing Ahead-of-Time or Just-in-Time compilation flows for AI workloads
• Transforming graphs or working with operator partitioning, scheduling, memory planning, or model optimisation
• Validating, benchmarking, profiling, or analysing AI model performance
• Developing compiler technologies, intermediate representations, or hardware abstraction layers
• Building automated tests and CI/CD workflows for large-scale software projects
• Applying AI-assisted development tools responsibly to improve engineering productivity and software quality

What You Will Learn and Develop
Interested in exploring how machine learning models move from high-level frameworks through the software stack to hardware acceleration?

This role provides opportunities to deepen expertise in machine learning runtime development and hardware-accelerated AI execution. The work spans the end-to-end AI software stack, from framework-level model execution and backend delegation through compiler flows to NGP acceleration.

Working collaboratively across Arm provides exposure to inference engines and runtimes, accelerator integration, operator partitioning and fallback mechanisms, AOT and JIT compilation, model validation and benchmarking, performance optimisation, and automated validation workflows.

There are also opportunities to build a broader understanding of how machine learning frameworks, software, compilers, and hardware come together to deliver efficient AI experiences on Arm technology.
Working at Arm
At Arm, we want our people to learn, contribute, and grow while working on technologies shaping the future of AI and computing. The role offers opportunities for professional development, collaboration with colleagues across our global engineering community, and exposure to challenging technical problems with real-world impact.

Arm provides a comprehensive range of employee benefits and support designed to help our people thrive at work and beyond. Benefits vary by location and can include support for health and wellbeing, financial wellbeing, time away from work, and professional development.

We want our recruitment process to be accessible and inclusive. Reasonable accommodations are available throughout the recruitment process, and we encourage candidates who require support to let us know so that appropriate adjustments can be considered.

If Skilled Worker sponsorship is required, Arm will meet costs associated with sponsorship for the employer only. Fees associated with the individual’s application, such as the visa application fee and Immigration Health Surcharge, will be the responsibility of the successful candidate.

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Accommodations at Arm
At Arm, we want to build extraordinary teams. If you need an adjustment or an accommodation during the recruitment process, please email (email protected). To note, by sending us the requested information, you consent to its use by Arm to arrange for appropriate accommodations. All accommodation or adjustment requests will be treated with confidentiality, and information concerning these requests will only be disclosed as necessary to provide the accommodation. Although this is not an exhaustive list, examples of support include breaks between interviews, having documents read aloud, or office accessibility. Please email us about anything we can do to accommodate you during the recruitment process.
Hybrid Working at Arm
Arm’s approach to hybrid working is designed to create a working environment that supports both high performance and personal wellbeing. We believe in bringing people together face to face to enable us to work at pace, whilst recognizing the value of flexibility. Within that framework, we empower groups/teams to determine their own hybrid working patterns, depending on the work and the team’s needs. Details of what this means for each role will be shared upon application. In some cases, the flexibility we can offer is limited by local legal, regulatory, tax, or other considerations, and where this is the case, we will collaborate with you to find the best solution. Please talk to us to find out more about what this could look like for you.

Equal Opportunities at Arm
Arm is an equal opportunity employer, committed to providing an environment of mutual respect where equal opportunities are available to all applicants and colleagues. We are a diverse organization of dedicated and innovative individuals, and don’t discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity, national origin, disability, or status as a protected veteran.

Listing found on arm.com via Cambridge Network. Always apply through the employer’s own posting.

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