Graduate Embedded AI Engineer - 12 month Fixed Term Contract

**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