Artificial Intelligence Developer Intern

We are looking for a motivated Artificial Intelligence Developer intern to contribute to the development, optimization, and deployment of AI solutions tailored for local and edge computing environments. This role involves working closely with open-source and open-weight AI models, custom training architectures for specific tasks, and addressing the challenges of running lightweight AI models on resource-limited edge devices. The intern will gain hands-on experience in cutting-edge AI technologies and collaborate with cross-functional teams to bring AI applications from concept to deployment.

Key Responsibilities
- Model Training & Fine-Tuning: Design, build, and train machine learning models. Develop custom training and fine-tuning pipelines using modern open-source datasets and frameworks.
- Open-Source & Open-Weight Ecosystem: Work extensively with state-of-the-art open-source and open-weight models such as Llama, Mistral, Whisper, Flux, and Stable Diffusion to solve practical problems.
- Edge Deployment: Quantize, optimize, and deploy lightweight AI models on client-side and edge platforms using frameworks like Transformers.js, ONNX Runtime, TensorRT, or WebGPU.
- Model Optimization: Implement optimization techniques including pruning, quantization (INT8/INT4), distillation, and compilation to reduce memory usage and latency while preserving model accuracy.
- Cross-Functional Collaboration: Partner with backend developers and hardware engineers to integrate embedded and edge AI models into end-user applications and hardware pipelines.

Required Qualifications
- Core AI/ML Skills: Solid understanding of machine learning and deep learning concepts, with hands-on experience in frameworks such as PyTorch, TensorFlow, or JAX.
- Open-Source Experience: Practical knowledge of exploring, fine-tuning, and evaluating models from repositories like Hugging Face and other open-source platforms.
- Edge & Web AI: Familiarity with edge runtime environments including Transformers.js, ONNX Runtime Web/Mobile, and TensorFlow Lite (TFLite).
- Programming Proficiency: Strong skills in Python, along with working knowledge of JavaScript/TypeScript or C++ for deployment in edge execution environments.

Preferred Qualifications
- Hardware Understanding: Awareness of hardware-level constraints and architectures such as GPU acceleration, Neural Processing Units (NPU), microcontrollers, Raspberry Pi, NVIDIA Jetson, or WebGPU contexts in browsers is highly desirable.

Interested candidates are encouraged to apply through the official CM IT Internship Program Portal. This internship offers a unique opportunity to work on innovative AI projects and gain valuable experience in deploying AI at the edge.