Deep Learning Intern, Model Optimization

Focus on optimizing state-of-the-art computer vision and deep learning models for deployment in industrial settings.
Research and apply model compression techniques, including knowledge distillation and quantization, to reduce latency and memory usage while preserving accuracy.
Design and run experiments to evaluate trade-offs between speed, size, and precision; report findings clearly.
Adapt models for constrained edge hardware to enable real-time robotic control and decision-making.
Collaborate with software and hardware teams to integrate optimized models into the production stack.
Proficient in Python and major DL frameworks (PyTorch, JAX, TensorFlow) with CV experience (Transformers, CNNs) and strong data-driven analysis.