Machine Learning Engineer

Machine Learning Engineer (OptiMax AI) OptiMax AI Limited is a cutting‑edge artificial intelligence company based in Hong Kong, dedicated to developing secure, controllable, and efficient enterprise‑grade private supply chain large models. Our vision is to become the "AI Decision Brain" that powers intelligent enterprise operations. Founded in September 2025, OptiMax AI is backed by a stellar technical vision and a top‑tier team, and is a key startup supported by the Hong Kong Innovation and Technology Commission's RAISe+ programme. We are AI‑empowered and data‑driven, committed to facilitating profound digital and intelligent transformation and decision‑making upgrades for global enterprises. About the Role As a Machine Learning Algorithm Engineer at OptiMax AI, you will be the creator of the core intelligence behind the "AI decision‑making brain." Your algorithm development will directly act on the most complex and challenging links in enterprise operations—from predicting market changes and optimizing production resources to foreseeing equipment failures and enabling precise production scheduling. You not only need to build accurate models but also deeply understand the pulse of the manufacturing industry, translating business problems into mathematical ones and solving them with stable and reliable code. Key Responsibilities Core Algorithm R&D & Optimization: Research, implement, and optimize machine learning algorithms suitable for complex industrial scenarios. End‑to‑End Solution Building: Lead the full lifecycle from business understanding, data exploration, feature engineering, and model training to online deployment and performance monitoring, ensuring algorithm models stably generate value in real‑world environments. In‑depth Industrial Data Mining: Conduct analysis of massive, high‑noise industrial data (such as sensor data, production logs, ERP/MES system data) to build a feature system capable of capturing complex patterns. Cross‑domain Collaboration: Work closely with operations research optimization algorithm engineers, data engineers, and product managers to jointly design and deliver end‑to‑end AI solutions integrating predictive and optimization capabilities. Technology Forecasting & Implementation: Continuously track cutting‑edge industry algorithms (such as time‑series prediction, anomaly detection, graph neural networks, reinforcement learning, etc.) and evaluate their application potential in industrial scenarios. Essential Qualifications Master's degree or above in Computer Science, Statistics, Operations Research, Industrial Engineering, or related fields, with experience in machine learning algorithm development. Solid mathematical foundation, proficient in probability theory, mathematical statistics, and linear algebra. Proficient in Python and major data science libraries, with an in‑depth understanding of at least one deep learning framework. Solid foundation in machine learning algorithms, familiar with both classic and cutting‑edge models. Excellent problem‑analysis and problem‑solving abilities, capable of independently undertaking the entire process from design to verification. Preferred Qualifications Doctoral degree in a related field. Data science project experience in manufacturing, supply chain, industrial automation, or related fields; familiarity with systems such as MES/ERP is preferred. Familiarity with classic operations research optimization problems and experience in joint debugging of predictive and optimization models is preferred. Experience in applying graph neural networks, reinforcement learning, or similar technologies in industrial scenarios. Experience in deploying algorithm models to production environments and familiarity with related technologies. #J-18808-Ljbffr