Graduate Embedded AI Engineer - 12 month Fixed Term Contract
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What you'll do
- Assist senior engineers in integrating and deploying trained AI/ML models onto embedded/edge platforms.
- Develop and modify software components using C/C++ and Python.
- AI model conversion, operator compatibility checks, custom operator development and integration with appropriate inference runtimes and hardware platforms.
- Build, run and test software on development boards or target hardware.
- Investigate software/model integration issues with guidance from experienced engineers.
- Develop integration tests and simple automation scripts.
- Use state of art development tools and develop automated processes for software builds, testing, model conversion, deployment and benchmarking.
- Contribute ideas, experiments and prototypes to investigate technical problems & potential improvements.
- Communicate effectively with team members and stakeholders, ensuring clear and concise information exchange.
What they're looking for
- Honours Bachelor's degree (NFQ Level 8 or equivalent) in Computer Engineering, Electronic/Electrical Engineering, Computer Science, Software Engineering, Artificial Intelligence, Robotics or a related technical discipline.
- Basic understanding of programming and software engineering principles.
- Working knowledge of C or C++ through academic, internship or personal-project experience.
- Working knowledge of Python.
- Familiarity with a Linux development environment.
- Familiarity with Git/version control.
- Basic understanding of machine-learning concepts, including training versus inference, datasets and model evaluation.
- Exposure to at least one ML framework such as PyTorch or TensorFlow.
- Basic understanding of System on Chip (SOC) architecture, embedded systems or constrained computing.
- Good analytical and problem-solving skills.
- Ability to communicate technical information clearly.
- Strong willingness to learn unfamiliar technologies.
Nice to have
- A Master's degree is beneficial but not required.
- ONNX / ONNX Runtime
- TensorFlow Lite
- PyTorch / ExecuTorch
- Model quantisation
- Pruning or model compression
- ARM-based processors
- GPU / NPU / DSP accelerators
Summarised by NextRaise from the employer’s description, which follows in full below.
Full description from employer
Valeo is a tech global company, designing breakthrough solutions to reinvent the mobility. We are an automotive supplier partner to automakers and new mobility actors worldwide. Our vision? Invent a greener and more secured mobility, thanks to solutions focusing on intuitive driving and reducing CO2 emissions. We are leader on our businesses, and recognized as one of the largest global innovative companies.
Mission
As part of the anSWer Embedded AI team, the Graduate Embedded AI Engineer works on the deployment, integration and validation of AI/ML models on embedded and edge computing platforms. Working under the guidance of experienced engineers, they apply software engineering, deep learning and embedded-system fundamentals to implement, test, benchmark and optimise AI solutions for target hardware. The role focuses on developing strong technical foundations while contributing to production-oriented engineering projects.
Responsibilities
Embedded AI Deployment
Assist senior engineers in integrating and deploying trained AI/ML models onto embedded/edge platforms.
Develop and modify software components using C/C++ and Python.
AI model conversion, operator compatibility checks, custom operator development and integration with appropriate inference runtimes and hardware platforms.
Build, run and test software on development boards or target hardware.
Investigate software/model integration issues with guidance from experienced engineers.
Develop integration tests and simple automation scripts.
Competencies:
Discipline Design Process Application: Demonstrate proficiency in applying the established Discipline design processes and methodologies.
Technical Learning: Actively develop knowledge in embedded systems, deep learning inference, AI deployment frameworks, target hardware architectures and software optimisation techniques through project work, mentoring and self-directed learning.
Development Automation and Efficiency
Use state of art development tools and develop automated processes for software builds, testing, model conversion, deployment and benchmarking.
Innovation:
Contribute ideas, experiments and prototypes to investigate technical problems & potential improvements. Innovation is expected, with technical direction and review provided by experienced engineers.
Collaboration and Influence:
Effective Communication: Communicate effectively with team members and stakeholders, ensuring clear and concise information exchange.
Profile
Education
Honours Bachelor's degree (NFQ Level 8 or equivalent) in Computer Engineering, Electronic/Electrical Engineering, Computer Science, Software Engineering, Artificial Intelligence, Robotics or a related technical discipline.
A Master's degree is beneficial but not required.
Experience
Applications from recent graduates with no commercial engineering experience are welcome. Relevant experience may include internships, university projects, final-year projects, research projects, hackathons, substantial personal/open-source projects, and maximum one year in a company after graduation.
Skills
Basic understanding of programming and software engineering principles.
Working knowledge of C or C++ through academic, internship or personal-project experience.
Working knowledge of Python.
Familiarity with a Linux development environment.
Familiarity with Git/version control.
Basic understanding of machine-learning concepts, including training versus inference, datasets and model evaluation.
Exposure to at least one ML framework such as PyTorch or TensorFlow.
Basic understanding of System on Chip (SOC) architecture, embedded systems or constrained computing.
Good analytical and problem-solving skills.
Ability to communicate technical information clearly.
Strong willingness to learn unfamiliar technologies.
Desirable / nice to have skills (not mandatory)
ONNX / ONNX Runtime
TensorFlow Lite
PyTorch / ExecuTorch
Model quantisation
Pruning or model compression
ARM-based processors
GPU / NPU / DSP accelerators
Embedded Linux
RTOS
Cross-compilation
CMake
Docker
CI/CD
Profiling/debugging tools
SIMD/vectorisation
Hardware/software interfacing
Job:
R&D Trainee/Apprentice/VIEOrganization:
PlatformSchedule:
Full timeEmployee Status:
Trainee (Fixed Term) (Trainee)Job Type:
GraduateJob Posting Date:
2026-08-26Join Us !
Being part of our team, you will join:
- one of the largest global innovative companies, with more than 20,000 engineers working in Research & Development
- a multi-cultural environment that values diversity and international collaboration
- more than 100,000 colleagues in 31 countries... which make a lot of opportunity for career growth
- a business highly committed to limiting the environmental impact if its activities and ranked by Corporate Knights as the number one company in the automotive sector in terms of sustainable development
More information on Valeo: https://www.valeo.com
Company
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