OptiMax AI

About Us

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.

Join us and help shape the future of enterprise intelligent decision-making!

About the Role

As a Large Model Algorithm Engineer at OptiMax AI, you will be the core bridge connecting cutting-edge AI research with reliable enterprise-level applications. You are not content with merely calling model APIs but delve deep into exploring their underlying mechanisms. Based on our mature system architecture and atop a unified underlying data platform, you will personally build, optimize, and deliver reliable, efficient enterprise-level large model intelligent systems.

Key Responsibilities

• Enterprise-Level Model Deployment & Operation: Responsible for the secure and reliable deployment of large models to on-premises environments or the cloud, ensuring continuous, stable, and efficient inference services.

• Domain Adaptation & Fine-Tuning: Conduct efficient instruction tuning and domain adaptation of foundation models based on enterprises' specific business data (such as supply chain, production logs, ERP data, etc.) to enhance their professional performance in vertical scenarios.

• Multi-Agent System Construction: Implement multi-agent collaboration frameworks to enable multiple models or modules to work synergistically, completing complex decision-making chains and tasks.

• Data Perception & Processing: Collaborate closely with data platforms and data engineers to establish an efficient data pipeline from enterprise data sources to model training and inference, ensuring models can "perceive" the latest and most relevant business data.

• Performance Optimization & Evaluation: Continuously optimize model inference speed, accuracy, and resource consumption, and establish a scientific evaluation system for quantitative testing and iterative tuning of model performance.

We're Looking For

Essential Qualifications:

• Master's degree or above in Computer Science, Artificial Intelligence, or related fields, with 3+ years of R&D experience in machine learning/natural language processing.

• Solid Python programming skills and proficiency in at least one mainstream deep learning framework such as PyTorch/TensorFlow.

• Experience in end-to-end large model projects, with an understanding of the details of core architectures like Transformer.

• Familiarity with at least one mainstream AI application development framework such as LangChain or LlamaIndex, with practical project experience.

• Familiarity with advanced application architectures such as RAG and Agent, with practical implementation experience.

• Excellent teamwork and communication skills, capable of clearly articulating complex engineering problems to team members.

Preferred Qualifications:

• Doctoral degree in a related field.

• Experience in AI projects within manufacturing, supply chain, or industrial sectors, with an understanding of relevant business scenarios and data characteristics.

• Experience in large-scale distributed training or inference optimization, familiar with optimization tools such as vLLM and TensorRT-LLM.

• Publications in top conferences or journals in related fields.