Researcher

JOB DESCRIPTION:

. LeadMultimodal Knowledge Curation Research: Research and develop thestate-of-the-art AI methods / algorithms for implicit knowledge extraction,capturing hidden human expertise such as communication strategies,problem-solving patterns, emotional intelligence cues, and decision-makingbehaviors across multimodal inputs (speech, conversation, visual cues, and bodylanguage).

. BuildData Pipelines and Research Prototypes: Design intelligent pipelines tocapture and synchronize multimodal interactions, and build functional researchprototypes (such as AI copilots, knowledge assistants, human-AI collaborationsystems, and multimodal reasoning systems).

. EstablishEvaluation & Benchmarking Frameworks: Design quantitative and qualitativeevaluation frameworks to assess knowledge extraction quality, explainability,interpretability, and generalization across diverse scenarios.

. TechnologyTransfer & PoC Delivery: Study, evaluate, and collaborate with other NEC globallabs to transition frontier multimodal AI capabilities into practical customertrials, proof-of-concept (PoC) projects, and industry solutions (e.g.,healthcare, customer service, smart enterprise).

. IPCreation & Academic Contributions: Invent and file patents for novelmultimodal AI technologies and represent NEC by publishing and presentingresearch at top-tier international conferences/journals and exhibitions.

. Ad-hocDuties:Perform any other ad-hoc research or operational duties as needed or assigned.

JOB REQUIREMENTS:

. At least a Master's degree (Ph.D. preferred) in Computer Science, Artificial Intelligence, Electrical/Computer Engineering, or a related field, with a focus on Multimodal Learning, Natural Language Processing, Computer Vision, or Speech/Audio Processing.

. A minimum of 2 years of hands-on experience in researching, developing, and deploying machine learning/deep learning models, with practical exposure to GPU and/or TPU/NPU environments. (Fresh Ph.D. graduates with relevant research publications in top-tier conferences/journals are welcome to apply).

. Deep technical expertise in Large Language Models (LLMs), Generative AI, multimodal representation learning, or human-centric AI.

. Proven proficiency in Python (PyTorch, TensorFlow, Hugging Face, etc.) and experience with C++ and/or Java, particularly in developing RESTful APIs and integrating modular AI services.

. Demonstrated ability to independently read, critique, and implement cutting-edge AI research papers and state-of-the-art architectures.

. Strong understanding of software engineering best practices, version control systems (Git), and GPU computing environments.

. Self-motivated and proactive, with strong problem-solving skills and a demonstrated ability to take initiative and drive applied research projects from conception to completion.