Machine Learning Scientist/Engineer – NLP/GenAI Foundation Models

Closed

Engineering Data Analyst AI/Artificial Intelligence Machine Learning NLP

Vị trí

Ho Chi Minh

Số lượng còn trống

4 person(s)

Phúc lợi

Lương tháng 13

Bảo hiểm nâng cao

Cấp laptop

Du lịch/Công tác

Đánh giá lương hàng năm

Bảo hiểm full lương

Tổng quan về công việc và trách nhiệm

We are seeking an experienced Machine Learning Scientist/Engineer with deep expertise in NLP/GenAI Foundation Models to join our innovative team. As a vital member of our AI department, you will play a significant role in designing, implementing, and deploying GenAI applications to enhance care delivery and quality for patients. The ideal candidate will bring technical proficiency, fluency with foundation models, a genuine interest in the medical domain, and strong critical thinking skills to the role. - Design and develop the next generation of NLP, ML & AI products and services for healthcare, collaborating with MLEs and software engineers to deploy them into production. - Improve processes and tools for generating ground truth to build models. - Lead model evaluation processes to ensure accuracy, fairness, and reproducibility. - Implement and design novel language model approaches inspired by relevant literature. - Stay up to date with the latest advancements in the field and implement state-of-the-art models from the literature for benchmarking. - Document model architectures, design decisions, and codebase to facilitate future maintenance and enhancements. - Work independently and collaboratively, manage priorities, and deliver high-quality results within project timelines.

Kỹ năng và kinh nghiệm tối thiểu

- Master's or PhD degree in ML, NLP, information retrieval, or a related field. - 3+ years of experience in training, pre-training, and fine-tuning NLP/GenAI models. - Fluent English communication - Experience with state-of-the-art NLP algorithms and AI models. Demonstrated experience with large language model techniques, including prompt optimization and parameter-efficient fine-tuning. - Experience building foundation models. - Experience in experimenting with and building architecture layers in neural networks, and constructing customized loss functions. - Experience with retrieval-augmented generation, model distillation, and reinforcement learning with human feedback (RLHF). - Experience with small and large language models, and multi-modal language models. - Familiarity with NLP similarity metrics and LLM-based evaluation frameworks. Extensive experience with TensorFlow or PyTorch, HuggingFace, Transformers, LangChain, vector databases, and cloud platforms (e.g., Azure). - Ability to work independently and collaboratively, manage priorities, and deliver high-quality results within project timelines.