2027 Fresh Grad Hire - AI Algorithm Engineer

moomoo; Hong Kong; On-site; HKD 700,000 - 1,200,000; Full time

Job summary

moomoo is hiring a research-oriented AI engineer in Hong Kong to work on investment agents, intelligent search, and personalized recommendations. You will participate in model training, evaluation, and deployment across product, engineering, and quantitative teams to deliver real business impact.

Ideal candidates have strong ML/DL fundamentals, hands-on Python and PyTorch experience, and a passion for advancing AI in financial contexts and fintech platforms.

Qualifications

• Bachelor's degree or above in Computer Science, Artificial Intelligence, Mathematics, Statistics, Automation, Financial Engineering, or related field.
• Solid foundation in machine learning and deep learning; knowledge of Transformers, LLMs, agents, or search/recommendation systems.
• Proficient in Python; familiar with PyTorch and data structures, algorithms, and engineering implementation.
• Strong problem analysis, experimentation, and ability to validate data-driven solutions in practical goals.
• Fluent in English; capable of technical communication and cross-team collaboration.

Responsibilities

• Research and optimize core algorithms including large language models, agents, RAG, and multimodal components, with data construction and evaluation.
• Deploy AI scenarios for investment agents, intelligent search, personalized recommendations, and financial analysis; collaborate across product, eng, and quant teams.
• Build and evolve the AI platform, knowledge bases, model services, and evaluation systems for scalable reuse.

Skills

Python

ML/DL

Transformers

RAG

Search & Reco

Data Analysis

Education

Bachelor's degree or above in CS/AI/Math/Statistics/Automation/FinEng

Tools

PyTorch

Pandas

NumPy

Git

Job description

About Us

The Futu AI team is dedicated to deeply applying artificial intelligence to financial investment and enterprise productivity scenarios. Our scope covers investment agents, intelligent search, recommendation, growth, financial analysis, AI customer service, AIGC, AI-native R&D tools, as well as a unified AI platform and infrastructure.

You will have the opportunity to participate in the intelligent upgrade of products such as Futubull and moomoo, and to contribute to the company-wide Agent platform and shared AI capabilities—enabling AI to directly improve users' investment experience, create business value, and boost organization productivity.

Why This Role

• Real, core scenarios: Work on investment agents, intelligent search, personalized recommendation, financial analysis, and enterprise AI applications, where algorithm performance can be validated quickly in real business.
• Full technical stack: Cover model training and optimization, Agent/RAG, search and recommendation, model evaluation, and AI platform capability building.
• Technology and business in equal measure: Collaborate with product, operations, and engineering teams to translate cutting-edge technology into user experience and business results.
• Multi-directional growth: Based on your strengths, contribute to one or more areas such as large models, agents, search and recommendation, financial algorithms, or the AI platform.

Key Responsibilities

• Core algorithm R&D and optimization: Participate in technical R&D in areas such as large language models, agents, RAG, multimodal, search and recommendation, and financial algorithms; carry out high-quality data construction, model training and post-training, evaluation analysis, and performance optimization.
• AI scenario implementation and business enablement: Drive the implementation of AI technology in scenarios such as investment agents, intelligent search, personalized recommendation, financial analysis, AI customer service, AIGC, and R&D efficiency improvement. Work with product, engineering, and quantitative teams to complete the full loop from requirements analysis and solution design to launch and validation.
• AI platform and capability accumulation: Participate in building the Agent platform, the Skill/MCP ecosystem, knowledge bases, model services, and automated evaluation systems; drive the modularization, servitization, and large-scale reuse of algorithm capabilities.

Requirements

• Bachelor's degree or above in Computer Science, Artificial Intelligence, Mathematics, Statistics, Automation, Financial Engineering, or a related field.
• Solid foundation in machine learning and deep learning; understanding of the fundamental principles of Transformers, large language models, agents, or search and recommendation systems.
• Proficient in Python; familiar with mainstream deep learning frameworks such as PyTorch; strong capabilities in data structures, algorithms, and engineering implementation.
• Strong problem analysis and experimentation skills; able to complete data analysis, solution design, model experimentation, and performance validation around practical goals.
• Passionate about AI technology and its real-world applications; keeps up with the latest progress in large models, agents, and AI engineering.
• Strong self-drive, learning ability, and communication and collaboration skills; able to read English technical materials.

Preferred Qualifications

• Project or internship experience in large model training and optimization, agents, RAG, search and recommendation, multimodal, or financial algorithms.
• Papers published at top academic conferences, or outstanding results in algorithm, programming, mathematics, or data science competitions.
• Contributions to high-quality open-source projects, or familiarity with technologies such as model post-training, reinforcement learning, retrieval optimization, inference acceleration, and model evaluation.
• Strong interest in financial markets such as stocks and options; experience in quantitative research, fintech projects, or AI product implementation.
• Fluent English & Chinese listening and speaking skills; ability to conduct work meetings, cross-team collaboration, and technical communication in English.

*Open to candidates graduating between January 2026 and August 2027.