Research Intern (NLP/ML, Multimodal, Knowledge Graph)

Key Skills

Effective communication skills, Machine learning techniques, Natural Language Processing (NLP), Python Programming, PyTorch, TensorFlow

Job Description

Sony AI is looking for highly motivated and skilled Research Interns specializing in Generative Language Models, Natural Language Processing/Machine Learning (NLP/ML), and Reasoning/Explainability. The ideal candidate will be a Ph.D. student or recent graduate with a strong research background and a passion for advancing the state-of-the-art in language understanding, generative reasoning, and graph embedding. The internship requires a minimum of 3 months duration; ideally, you can commit for 6 months (early start dates preferred). During the internship, you will collaborate closely with mentors on all research aspects, from problem definition to developing innovative ML solutions and presenting findings at top-tier publication venues.

Roles and Responsibilities

• Conduct fundamental and applied research in generative AI and knowledge graph, focusing on tasks such as large-scale knowledge graph construction, graph embedding, representation learning and reasoning, and scalable training methods.
• Contribute to the development of libraries and tools to support both research and business objectives.
• Prepare reports and deliver presentations for internal audiences.
• Publish impactful research outcomes in top-tier conferences.

Required Qualifications and Skills

• Currently has, or is in the process of obtaining Ph.D. degree in computer science or a related field.
• Demonstrated expertise or publications in machine learning, unsupervised/semi-supervised methodologies, NLP, multimodal learning, representation and reasoning, efficient and scalable training, etc.
• Exposure to large-scale text data processing and graph embedding techniques.
• Excellent analytical and programming skills (Python) and experience with large-scale deep learning frameworks (TensorFlow, PyTorch).
• Ability to communicate research in a clear and precise manner.