Machine Learning Engineer for Computer Vision

As a Machine Learning Engineer at Apple, you will have the opportunity to impact the future of manufacturing through cutting-edge ML techniques. Your role will involve a wide variety of skills, innovation, and working on groundbreaking applications of machine learning in research and implementation. Your work will have a significant impact on billions of users worldwide by influencing globally recognized products" supply chain. - Collaborate with different engineering and operations teams to develop ML solutions for various vision and language-based tasks and projects. - Deliver ML technologies aligned with fast-paced new technology and short product lifecycle, ensuring top-tier product quality and reliability. - Craft, design, and implement machine learning strategies for the iPhone, Mac, and iPad supply chains to shape the future of manufacturing systems. - Develop and deploy machine learning models to optimize processes, automate quality control, and enhance operational efficiency in manufacturing environments. - Fine-tune Large Language Models (LLMs) and apply them in combination with Computer Vision (CV) techniques to tackle challenges in manufacturing. Minimum Qualifications: - Experience developing deep learning models such as CNNs, Vision Transformers, or YOLO for image-based tasks in production systems. - Proven research and practical experience in developing algorithms for image processing, content-based video/image analysis, object detection, segmentation, and tracking. - Proven experience in fine-tuning LLMs for domain-specific use cases such as document analysis and operational efficiency. - A Master's degree in computer science, Machine Learning, or a related field with 3+ years of industry experience in Machine Learning, Computer Science, Data Science, or related areas. - iOS CoreImage/CoreML and native App development experience is advantageous. - Experience deploying ML models in cloud environments (AWS, GCP, or Azure) for scalable production use. Preferred Qualifications: - Strong grasp of deep learning principles in both Computer Vision and Natural Language Processing (NLP). - Familiarity with LLM architectures like BERT, GPT, and experience fine-tuning these models for improved performance in manufacturing settings. - Knowledge of machine learning and Deep Learning libraries such as PyTorch, OpenCV, Hugging Face, is essential. - Proven ability to implement, improve, debug, and maintain machine learning models. - Familiar with version control systems such as Git. - Strong optimization and debugging skills. - Self-motivated, responsible, excellent written and verbal interpersonal skills. - Experience with handling and visualizing very large data sets and creating performance reports.,