MQA - Data Scientist on Natural Language

Summary Posted: Nov 28, 2023 Weekly Hours: 40 Role Number: 200523087 Apple is a place where extraordinary people gather to do their best work. Just be ready to dream big. If you are the kind of students who are passionate on pursuing excellence, embracing challenges, enjoying work with others, learning new things along the way, Apple is the right place for you. MQA team is a horizontal team in Manufacturing Design, responsible for ensuring the sustainability of high quality requirements compliance throughout MD supplier chain. Our goal is to provide effective and efficient monitoring of Apple's quality requirements compliance, while also proactively seeking out opportunities for continual improvement and sharing best practices cross LOBs in a systematic and creative way. As a MQA Data Scientist Intern focusing on natural language, you will work closely with team to understand txt data analysis needs and challenges. Our primary focus is developing applications such as RAG (Relevance Analysis and Generation), Agents, and other NLP/LLM-driven tools that empower MQA team to optimize workflow, improve efficiency, and reduce costs. Your contributions will directly impact the success of our projects, and your innovative thinking will help shape the future of AI in the manufacturing industry. Key Qualifications Key Qualifications Strong understanding of Natural Language Processing (NLP) and machine learning methodologies. Experience with deep learning frameworks such as TensorFlow or PyTorch. Working knowledge of Python and experience in data analysis and modeling. Strong problem-solving and analytical skills, with a focus on practicality and real-world application. Excellent communication and collaboration skills, with the ability to work effectively in a team environment. Passion for AI and a genuine interest in its impact on the manufacturing industry. Experience with developing applications or tools based on LLM as plus Understands in designing, constructing, and maintaining knowledge graphs, with knowledge in graph databases (e.g., Neo4j, NebulaGraph), ontology design, and semantic querying languages (e.g., SPARQL, nGQL) as a great plus Understanding of cloud-based computing platforms, like AWS or GCP as plus Understanding of the manufacturing industry and its challenges as plus Known with RAG (Retrieval-augmented generation) or Agents concepts as plus Description Description You will be directly responsible for building revolutionary applications to transform the manufacturing industry, such as Response Generation (RAG) and Agents, leveraging your expertise in Natural Language Processing (NLP) and Machine Learning. Designing, developing, and optimizing NLP-based applications that can efficiently process and analyze vast amounts of text data generated in the manufacturing industry. Integrating state-of-the-art large language models to enhance the capabilities of our applications, enabling them to generate human-like responses and perform advanced language understanding tasks to streamline engineer workflows. Design and implement machine learning models that can accurately process language data, perform sentiment analysis, entity recognition, named entity recognition, and other relevant tasks. Maintain a clean and well-documented codebase will be essential as we strive for code reusability and collaboration within the team. Actively research and keep abreast of the latest advancements in NLP and large language models, proactively proposing innovative solutions and improvements for our applications. Education & Experience Education & Experience MS/PhD in Engineering/Computer Science/EE Machine learning engineering background are strongly preferred. Additional Requirements Additional Requirements