Intel

Internship role focused on applied research and productization of Vision-Language Models (VLM) and Vision-Language-Action (VLA) models, including pre-training, fine-tuning, alignment, data pipelines, fusion strategies, action components, and model optimization for efficient deployment on Intel hardware. The role involves evaluating models and potentially publishing results.

Intel's AI Solutions Group is seeking an MSc/PhD student to work on state-of-the-art AI capabilities for chip development. The role involves solving high-value problems using ML, DL, and LLMs, from ideation and research to preparing solutions for deployment. Requires strong Python, ML/DL knowledge, and familiarity with AI tools like PyTorch or Scikit-learn.

Senior Principal Engineer in AI Applied Research at Intel, focusing on applying AI/ML to logic IP design and semiconductor manufacturing. The role involves conducting applied research, developing proof-of-concept models, and implementing solutions to demonstrate business value, requiring expertise in deep learning, ML, RL, NLP, GNNs, and time-series. The position emphasizes leadership, influencing partners, and mentoring technical leaders.

Internship role focused on the research and application of Vision-Language-Action (VLA) algorithms in robot scenarios. Responsibilities include VLA data collection, model fine-tuning, performance testing, problem analysis, and optimization using Python and frameworks like lerobot, PyTorch, and TensorFlow. The role involves improving model adaptability and execution accuracy for robot systems.

AI Software Engineering Intern at Intel contributing to the design, development, and optimization of AI software solutions across computer vision, machine learning, and deep learning. Responsibilities include implementing and tuning models, conducting applied research, and assisting with system-level deployment.