AI Engineer, Digital Venture

Makro PRO is a leading e-commerce company based in Thailand, dedicated to providing innovative and seamless shopping experiences for our customers. We are an exciting new digital venture by the iconic Makro. Our proud purpose is to build a technology platform that will help make business possible for restaurant owners, hotels, and independent retailers, and open the door for sellers. Makro PRO brings together the best talent across multi-nationals to transform the B2B marketplace ecosystem. We welcome bold, energetic, and thoughtful people who share our belief in collaboration, diversity, excellence, and putting customers at the heart of our work

Take your career to new heights in the future of B2B e-commerce. Join our team and help us build Southeast Asia’s next unicorn.

We are seeking a AI / Machine Learning Engineer skilled in both ML model development and backend engineering, with a strong foundation in deep learning and Thai language NLP. The ideal candidate will combine hands-on technical ability with a passion for building production-grade AI systems that enhance search and recommendation experiences for millions of users.

Key Responsibilities

1. Research & Model Development

• Read, interpret, and replicate academic and applied research papers to develop innovative ML and deep learning models.
• Apply and fine-tune deep learning architectures including CNNs, RNNs, Transformers, and Siamese networks for search and recommendation systems.
• Implement ranking and relevance optimization techniques such as Learning to Rank, Two Towers, XGBoost, reranking, relevancy tuning, and collaborative filtering.
• Build and train embeddings for improving semantic understanding and personalization.

2. Thai Language NLP

• Develop NLP models tailored for the Thai language, addressing tokenization, fuzziness, and non-space segmentation challenges.
• Implement solutions for vector similarity, closest word matching, and context-aware text embeddings.

3. Deep Learning & GPU Training

• Design, train, and optimize deep learning models using TensorFlow or PyTorch.
• Efficiently utilize GPU infrastructure for large-scale model training and fine-tuning.
• Conduct hyperparameter tuning and experiment tracking for continuous model improvement.

4. Backend Integration

• Integrate ML and deep learning models into production systems via Python and JavaScript (Node.js) backends.
• Develop and maintain REST APIs for model inference and search functionality.
• Debug, fix, and merge backend issues using Git-based workflows.

5. Model Deployment & Operations

• Deploy and manage ML pipelines in production environments.
• Ensure models are scalable, low-latency, and fault-tolerant.
• Work closely with data engineers and backend developers to ensure seamless integration and monitoring.
  

6. Collaboration & Delivery

• Collaborate cross-functionally to deliver measurable improvements in search relevance and user engagement.
• Focus on hands-on, results-oriented solutions rather than purely theoretical models.