About this role
Job Requirements
At Quest Global, it’s not just what we do but how and why we do it that makes us different. With over 25 years as an engineering services provider, we believe in the power of doing things differently to make the impossible possible. Our people are driven by the desire to make the world a better place—to make a positive difference that contributes to a brighter future. We bring together technologies and industries, alongside the contributions of diverse individuals who are empowered by an intentional workplace culture, to solve problems better and faster.
Overview
We are looking for a motivated AI Engineering Intern to contribute to the development of an Agentic Edge AI Studio, a multi-agent framework designed to automate AI model deployment for edge devices. The internship offers hands-on exposure to AI/ML deployment, edge AI optimization, MLOps automation, and agent-based systems.
Key Responsibilities
- Study and understand existing AI deployment toolchains and workflows.
- Develop and integrate automated deployment pipelines for edge AI applications.
- Build workflows to perform model compatibility analysis, validation, and performance reporting.
- Assist in implementing AI agent-based mechanisms for automated diagnosis and corrective actions during deployment.
- Support model optimization activities such as pruning, quantization, and compilation.
- Validate deployed models using simulators and target hardware platforms.
- Measure and analyse deployment metrics including accuracy, latency, memory utilisation, and deployment effort.
- Document findings, create technical reports, and present PoC demonstrations.
We are known for our extraordinary people who make the impossible possible every day. Questians are driven by hunger, humility, and aspiration. We believe that our company culture is the key to our ability to make a true difference in every industry we reach. Our teams regularly invest time and dedicated effort into internal culture work, ensuring that all voices are heard.
We wholeheartedly believe in the diversity of thought that comes with fostering a culture rooted in respect, where everyone belongs, is valued, and feels inspired to share their ideas. We know embracing our unique differences makes us better, and that solving the worlds hardest engineering problems requires diverse ideas, perspectives, and backgrounds. We shine the brightest when we tap into the many dimensions that thrive across over 21,000 difference-makers in our workplace.
Work Experience
Required Skills
- Basic understanding of Machine Learning and Deep Learning concepts.
- Programming experience in Python.
- Familiarity with AI frameworks such as TensorFlow, PyTorch, or ONNX.
- Understanding of software development practices and debugging techniques.
- Knowledge of Linux development environments.
- Good analytical and problem-solving skills.
Preferred Skills
- Exposure to Edge AI deployment workflows.
- Knowledge of model optimisation techniques such as quantization and pruning.
- Familiarity with embedded systems, MCUs, or edge computing platforms.
- Understanding of AI agents, agentic workflows, or MLOps concepts.
- Experience with Git and collaborative software development.
Learning Outcomes
During this internship, the candidate will gain practical experience in:
- Edge AI deployment automation.
- AI model optimisation techniques.
- Agentic AI system development.
- MLOps and deployment workflows.
- Embedded AI validation and benchmarking.
- Technical documentation and PoC development.
Deliverables
By the end of the internship, the intern is expected to contribute to:
- A working automated AI deployment workflow.
- Model compatibility and validation framework.
- Agent-assisted failure diagnosis and recovery mechanism.
- Hardware/simulator benchmarking results.
- Final demonstration, documentation, and user guide.