Suggested rewrite: Led a cross-functional initiative that improved [business outcome] by [measurable result], demonstrating experience relevant to this role...
Software Engineer – Edge AI
- Remote from
- EMEA
- Salary
- Undisclosed
- Department
- Software Engineering
- Employment
- Full Time
- Experience
- Open level
- Published
- Apply before
- 7 Dec 2026
- Listing views
- 29
- Application actions
- 2
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About this role.
This is an exciting opportunity for a software engineer passionate about open source software, Linux, edge computing, and AI. Come build a rewarding, meaningful career working with the best and brightest people in technology at Canonical, a growing international software company.
Your role will be to help us provide easy-to-deploy, secure, and customizable edge AI solutions, specifically focusing on Inference Snaps. You will work on designing and implementing silicon-optimized application packages for AI/ML inference, targeting devices from embedded systems to powerful gateways. Linux will be at the core of your everyday challenges.
In our team we value collaboration, peer reviews, good integration/unit testing, and writing maintainable code. General knowledge and experience with Linux as a developer platform is required.
What you’ll do
- Collaborate proactively with a distributed team
- Develop and maintain open-source AI/ML inference application packages
- Debug issues and produce high-quality code to fix them
- Review code produced by upstream and/or other engineers at Canonical
- Discuss ideas and collaborate on finding good solutions
- Experiment with Ubuntu Core and showcase industry-grade Edge AI solutions
- Secure deployment of AI inference platforms on Linux
- Build optimized AI solutions for local inferencing on Ubuntu
- Work from home with global travel 2 to 4 weeks for internal and external events
Who you are
- Proven track record of at least 3 years of professional software development using Go or C++.
- Experience working on and developing applications for Linux
- You have interest and experience with a few of the following:
- Containers (docker, kubernetes)
- Snap, debian, or RPM packaging
- Bash scripting
- CI/CD (GitHub Actions, GitLab CI, etc)
- Local AI/ML inference frameworks
- Hardware accelerators: GPU, NPU
- You value soft skills, communication and advocacy, and are passionate, enterprising, thoughtful, and self-motivated
- You have a Bachelor’s or equivalent in Computer Science, STEM or similar degree
Canonical is a growing international software company that works with the open-source community to deliver Ubuntu, the world’s best free software platform. Our services help businesses worldwide reduce costs, improve efficiency and enhance security with Ubuntu.
We are proud to foster a workplace free from discrimination. Diversity of experience, perspectives, and background create a better work environment and better products. Whatever your identity, we will give your application fair consideration.
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Sample interview questions
I would first identify runtime dependencies, model assets, hardware requirements, and security constraints. I would create a reproducible package, preferably using Snap where confinement and transactional updates are beneficial, then validate installation and operation across the supported device architectures. I would automate builds and tests in CI and document configuration, model updates, and rollback procedures.
I would establish a baseline for latency, throughput, memory use, CPU utilization, and accelerator utilization. I would profile the application and runtime, verify model format and accelerator delegation, inspect logs and system resource contention, and compare results with a controlled reference environment. Based on the findings, I would optimize the bottleneck and add regression benchmarks to prevent recurrence.
Key considerations include minimizing the software footprint, using signed and verified packages, applying least-privilege permissions, isolating workloads, protecting model and credential assets, and maintaining a reliable update path. I would also ensure that logs do not expose sensitive data and that vulnerabilities in dependencies can be tracked and patched quickly.
I focus reviews on correctness, maintainability, security, testing, and consistency with project conventions. I provide specific and respectful feedback, explain the reasoning behind requested changes, and distinguish blocking concerns from optional suggestions. I also treat reviews as a collaborative learning process and make sure my own changes are small, well-tested, and clearly documented.
In a typical approach, I would reproduce the issue in a controlled environment, collect application and system-level diagnostics, and reduce the failure to the smallest reproducible case. I would isolate whether the root cause was in the application, dependency, packaging, kernel interface, or device configuration, implement and test a focused fix, and document the outcome. I would then add automated coverage or monitoring to catch similar failures earlier.
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