MaxiPro (Asia) Limited Hiring! Full Time Machine Learning Engineer in Hong Kong - Ricebowl

We are seeking a highly skilled and experienced Machine Learning Engineer to become the founding technical pillar of our new Enterprise AI initiative. In this critical role, you will be responsible for designing, building, and deploying scalable AI systems from the ground up.

You will lead the development of our core AI capabilities, which include an intelligent customer service system (RAG-based), automated copywriting tools, market intelligence agents, and demand forecasting models. This is a unique opportunity to shape the AI architecture of the company and directly impact our operational efficiency and business growth.

• AI Architecture & Infrastructure: Design and implement the foundational end-to-end machine learning infrastructure and data pipelines required to support enterprise-grade AI applications.
• LLM Integration & RAG Development: Build and deploy robust Retrieval-Augmented Generation (RAG) systems for our customer support chatbot and internal knowledge bases, integrating with state-of-the-art LLM APIs (e.g., OpenAI, Anthropic) or fine-tuning open-source models (e.g., Llama 3).
• Model Deployment & MLOps: Own the lifecycle of ML models from development to production. Establish CI/CD pipelines for ML, ensure model monitoring, manage data drift, and maintain high system availability and scalability.
• Predictive Modeling: Collaborate with business units to develop and deploy time-series forecasting models (e.g., LSTM, XGBoost) to optimize inventory management and demand prediction.
• Market Intelligence Agents: Develop web scraping and NLP pipelines (sentiment analysis, entity extraction) to monitor competitor activities and market trends automatically.
• Technical Leadership: Act as the primary technical expert on AI/ML within the company. Evaluate new technologies, make build-vs-buy decisions, and eventually mentor junior engineers and data scientists as the team expands.

• 3+ years of professional experience in software engineering, with at least 2 years specifically focused on deploying Machine Learning / AI systems into production environments.
• Proven track record of building and scaling data-intensive applications and ML pipelines.

• Programming Languages: Expert proficiency in Python. Familiarity with other languages (e.g., Go, C++, JavaScript) is a plus.
• AI/ML Frameworks: Strong hands-on experience with modern LLM frameworks (e.g., LangChain, LlamaIndex) and deep learning libraries (e.g., PyTorch, TensorFlow, Scikit-Learn).
• Cloud & Infrastructure: Extensive experience with cloud platforms (AWS, GCP, or Azure). Proficiency in containerization and orchestration tools (Docker, Kubernetes).
• Data Engineering: Solid understanding of databases (SQL/NoSQL), vector databases (e.g., Pinecone, Milvus), and data processing tools (e.g., Spark, Kafka).
• MLOps: Experience with model registry, tracking, and monitoring tools (e.g., MLflow, Weights & Biases, Prometheus/Grafana).

• Engineering Mindset: You prioritize system reliability, security, and scalable architecture over merely achieving high model accuracy in a notebook.
• Problem Solver: Ability to translate complex business requirements (e.g., reducing inventory costs, automating customer service) into practical technical solutions.
• Communication: Excellent verbal and written communication skills. Ability to explain complex technical concepts to non-technical stakeholders.
• Pioneer Spirit: Comfortable working in an ambiguous, zero-to-one environment and eager to take ownership of the entire AI tech stack.