Agent Application Algorithm Engineer

Shopee; Singapore; On-site; SGD 180,000 - 260,000; Full time

Job summary

Sea Group is building a strategic AI department focused on generative AI to transform human connection and social interaction. Join a team developing multilingual AI ecosystems and MaaS platforms, driving production-level, multimodal AI applications in a fast-paced environment.

The role emphasizes building advanced Agent systems, memory architectures, multimodal RAG, and tool integrations, with a focus on scalable, high-quality AI deployments across Southeast Asia.

Qualifications

• Minimum 2 years of experience in computer vision, multimodal AI, or generative AI with production delivery.
• Familiarity with vision-language models (VLMs) like Qwen-VL, InternVL, GPT, Gemini; diffusion and video generation models.
• Master's degree or above in AI, CS, Mathematics, or related field.
• Strong programming skills; proficient in PyTorch; familiar with distributed training frameworks such as DeepSpeed and Megatron.
• Experience with LLM training/inference, data synthesis and filtering, prompt engineering and evaluation, deployment, and prototype development.
• Ability to collaborate across teams to drive research-to-deployment closed-loop workflows.

Responsibilities

• Advance multimodal understanding and generation pipelines; improve image/video generation quality and consistency.
• Develop core Agent logic: planning, tool-calling, multi-turn dialogue, memory, RAG, context engineering, multi-agent collaboration.
• Lead pre-training and post-training for vertical domains; build datasets and data pipelines; design RL reward models and improved reasoning.”
• Build long-term/short-term memory architectures to enhance immersion and consistency in long contexts.
• Develop multimodal RAG systems: recall, ranking, long-text processing, multi-document synthesis.
• Design and tune prompts; optimize context management for product needs.
• Create rigorous quantitative evaluation plans aligned with product requirements; monitor metrics for agent/model optimization.
• Explore innovative AI applications.

Skills

Computer vision

Multimodal AI

Generative AI

PyTorch

DeepSpeed

Megatron

LLM training

Prompt engineering

LangGraph

Google Agent Development Kit

OWL

Cursor

Claude Code

Video generation

Education

Master's degree in AI/CS

Tools

PyTorch

DeepSpeed

Megatron

LangGraph

Google Agent Development Kit

Cursor

Claude Code

Job description

About Us

Sea Group is establishing a brand-new, strategic AI department. This department is dedicated to exploring the transformative potential of generative AI in revolutionizing human connection, self-expression and communication diversity, and social interaction. We are building the next generation of AI-native applications and a comprehensive Model-as-a-Service (MaaS) product support system. Based on massive multi-country data, we are building a leading multilingual AI ecosystem from the ground up. We look forward to more outstanding talents joining us to build leading Southeast Asian multilingual models and explore innovative AI-native applications.

About The Team

Sea Group is establishing a brand-new, strategic AI department. This department is dedicated to exploring the transformative potential of generative AI in revolutionizing human connection, self-expression and communication diversity, and social interaction. We are building the next generation of AI-native applications and a comprehensive Model-as-a-Service (MaaS) product support system. Based on massive multi-country data, we are building a leading multilingual AI ecosystem from the ground up. We look forward to more outstanding talents joining us to build leading Southeast Asian multilingual models and explore innovative AI-native applications.

The AI application team focuses on the intersection of social connectivity and artificial intelligence. Our mission is to leverage LLMs to create digital personas that can act as personal assistants and social bridges. This team operates with a startup's agility backed by our Group's robust resources, aiming to define how humans interact in the AI era.

Job Description

• Optimize AIGC content generation quality by advancing multimodal understanding of images, audio, and video; improving image and video generation pipelines; and addressing generation consistency issues.
• Build core Agent logic, including but not limited to task planning and orchestration, tool calling, multi-turn dialogue management, memory, RAG, context engineering, and multi-agent collaboration.
• Lead Continuous Pre-training and Post-training for vertical domains and business scenarios, including building high-quality datasets and data pipelines, designing RL reward models, improving instruction following and reasoning capabilities, task completion, role-playing, anthropomorphic and personalized dialogue, proactive/reactive immersive multimodal conversation experiences, and enhancing the model's IQ and EQ.
• Build long-term and short-term memory architectures, addressing issues such as forgetting and attention dispersion in long contexts, and improving immersion and consistency in long-term user interactions.
• Build multimodal RAG systems, including development and optimization of key modules such as recall, ranking, long-text processing, and multi-document synthesis.
• Develop the Agent's tool layer, integrating external APIs and MCP such as search, code interpreters, browsers, sandboxes, and third-party services.
• Design and tune prompts and context management, with tailored optimization for different product requirements.
• Design scientifically rigorous quantitative evaluation systems and plans aligned with product requirements; continuously monitor product metrics and provide guidance for Agent and model optimization.
• Explore innovative AI applications.

Requirements

• A minimum of 2 years of experience in computer vision, multimodal AI, or generative AI, with hands-on experience delivering production projects. Familiarity with the principles and applications of mainstream vision-language models (VLMs), such as Qwen-VL, InternVL, GPT, and Gemini series, as well as diffusion and video generation models.
• Master's degree or above in Artificial Intelligence, Computer Science, Mathematics, or a related field.
• Strong programming skills; proficient in PyTorch; familiar with distributed training frameworks such as DeepSpeed and Megatron.
• Strong experience with techniques and principles of LLM training/inference, including but not limited to data synthesis and filtering, model training optimization, prompt engineering, evaluation, deployment, and prototype development.
• Strong problem analysis and resolution skills; sustained interest and curiosity in frontier AI technologies and applications; strong self-drive; able to collaborate closely with teams to drive a full closed loop from research to deployment.
• Good development experience with Agent frameworks such as LangGraph, Google Agent Development Kit, or OWL.
• Strong engineering capabilities; familiar with AI development tools such as Cursor and Claude Code; proactive mindset for improving efficiency.
• Prior project experience in areas such as Agentic reinforcement learning, virtual character generation, multimodal interaction, personality modeling, or memory will be a strong plus.