Multimodal Large Model Algorithm Engineer

WECHAT INTERNATIONAL PTE. LTD.; Singapore; On-site; SGD 60,000 - 80,000; Full time

Job summary

A leading technology company in Singapore is seeking a talented individual to conduct research and development of multimodal large model technologies. The ideal candidate will have a Master’s degree or higher in fields such as Computer Science or Machine Learning, strong engineering skills, and the ability to work on innovative solutions for complex problems. Familiarity with deep learning frameworks and a solid research background in multimodal understanding are essential for this role.

Qualifications

• Master’s degree or higher in Computer Science, Machine Learning, or related fields.
• Solid research background in multimodal understanding and familiarity with algorithms.
• Proficiency in deep learning frameworks like TensorFlow or PyTorch.

Responsibilities

• Conduct research and development of multimodal large model technologies.
• Track algorithms in multimodal large models and evaluate these models.

Skills

Deep learning frameworks

Programming languages (C/C++, Java, Python)

Multimodal understanding

Teamwork and communication skills

Technical curiosity

Education

Master’s degree or higher in Computer Science or related fields

Tools

TensorFlow

PyTorch

DeepSpeed

Megatron-LM

Job description

Job Description

• Conduct research and development of multimodal large model technologies, including cross-modal alignment and multimodal understanding tasks, to build industry-leading multimodal large models.
• Continuously track state-of-the art algorithms in multimodal large models, participate in the design, training, optimization, and evaluation of these models, and promote their application in business scenarios.

Job Requirements

• Master’s degree or higher in Computer Science, Machine Learning, Artificial Intelligence, Applied Mathematics, or related fields.
• Solid research background in multimodal understanding (e.g., natural language processing, computer vision, speech understanding/generation), with familiarity in mainstream models and algorithms such as CLIP, LLaVA, VALL-E, etc.
• Proficiency in deep learning frameworks like TensorFlow or PyTorch; knowledge of distributed training frameworks (e.g., DeepSpeed, Megatron-LM) and practical experience in multi-node/multi-GPU distributed training.
• Strong engineering skills with proficiency in at least one programming language: C/C++, Java, or Python.
• Publication record in top-tier conferences (e.g., ICLR, NeurIPS, CVPR, ICCV, ECCV, ACL, EMNLP) is preferred.
• Excellent learning ability, technical curiosity, and strong teamwork and communication skills.