Machine Learning Engineer Graduate (E-Commerce)

Key Responsibilities

• Architect and develop sophisticated LLM-based systems to process high-dimensional unstructured data (e.g., text, logs, conversations) from diverse sources.
• Define and implement complex semantic understanding frameworks, including fine-grained intent classification and entity extraction, to achieve deep contextual awareness.
• Apply state-of-the-art techniques to enhance model performance, including Instruction Tuning, RLHF/DPO, and Contextual Prompt Engineering.
• Optimize model serving for production environments using quantization, distillation, and efficient attention mechanisms (e.g., FlashAttention, vLLM).

Qualifications

• Individuals who are completing or have recently completed a PhD's degree in Computer Science, Engineering, Math, Statistics, or a related discipline.
• Experience in one or more of the following fields: Machine Learning, Natural Language Processing (NLP), or Computer Vision.
• Proficiency in software development with at least one of the following programming languages: C++, Python, Go, or Java.

Preferred Qualifications

• Experience in fine-tuning, distillation, or reinforcement learning for large language models in conversational AI applications.
• Proficiency in multilingual NLP, machine translation, and cross-lingual dialogue modeling.
• Experience in developing and optimizing e-commerce video and product multimodal large models, combining LLMs with video/product representations to support tasks like multimodal classification, video QA, and cross-modal retrieval.
• A strong understanding of e-commerce policies, dispute resolution workflows, and merchant-buyer interactions to inform AI service design.

Successful candidates must be able to commit to an onboarding date by the end of the year. Please state your availability and graduation date clearly in your resume.