AI Agent Engineer: Multiturn Dialogue & Post-Training ML

Shopee; Singapore; On-site; SGD 120,000 - 180,000; Full time

Job summary

Sea Group is building a new AI department focused on multilingual models and MaaS. We seek an experienced ML/NLP engineer to design a consumer-facing Shopping Agent, develop post-training pipelines, and optimize dialogue accuracy and product relevance.

You will collaborate with product, engineering, and operations teams to deploy capabilities at scale, with emphasis on data alignment, evaluation, and cost efficiency.

Qualifications

• Master’s degree or higher in CS, AI, or related field.
• 3+ years in ML/NLP, search/recommendation, or LLM apps.
• Hands-on with post-training methods such as SFT, DPO, PPO/RLHF, or Reward Modeling.
• Familiar with Megatron-LM, veRL, or DeepSpeed and basic distributed training.
• Experience with Agent, Function Calling, Tool-use, multi-turn dialogue, and LLM evaluation.
• Strong Python, engineering, data-analysis, and production problem-solving skills.
• Experience in e-commerce AI or large-scale post-training is a plus.

Responsibilities

• Design and optimize a consumer-facing e-commerce Shopping Agent covering intent understanding and dialogue.
• Develop and implement post-training pipelines including SFT/DPO/PPO-RLHF and Reward Modeling.
• Improve tool-use accuracy, instruction following, product relevance, and factual consistency.
• Build post-training datasets and evaluation systems with human and automated metrics.
• Drive continuous optimization via offline evaluation, A/B tests, and latency/cost improvements.
• Collaborate with product, engineering, search/recommendation, and operations teams to deploy Agent capabilities.

Skills

Python

NLP

Distributed training

Post-training methods

LLM evaluation

Problem-solving

Education

Master’s degree in CS/AI

Tools

Megatron-LM

DeepSpeed

veRL

Job description

Sea Group is building a new AI department focused on multilingual models and MaaS. We seek an experienced ML/NLP engineer to design a consumer-facing Shopping Agent, develop post-training pipelines, and optimize dialogue accuracy and product relevance.

You will collaborate with product, engineering, and operations teams to deploy capabilities at scale, with emphasis on data alignment, evaluation, and cost efficiency.