Junior/Senior Machine Learning Engineer

About this role

About LINE MAN Wongnai We are Thailand’s leading provider of On-Demand Services (ODS), Merchant Digital Solutions(MDS), and Payment and Financial Services (PFS). We build technology to help Thai people live better, to empower all local businesses by creating an end-to-end food ecosystem through our channel. Connected consumers, riders, and local businesses and improved the daily life of all parties with restaurants nationwide. And because we are local, we provide the deepest variety and services that are tailor-made for Thai people. We are currently looking to hire a Machine Learning Engineer to join us on this exciting journey and working in a fast-paced environment, you will bring your expertise and skills to tackle the challenges that impact millions of people on our journey to become the No.1 food platform in Thailand. What you’ll Do: Accelerate the ML Lifecycle : Design and scale MLOps infrastructure and agentic AI workflows to speed up end-to-end model development, validation, and CI/CD deployment pipelines. Bridge Engineering & Data Science : Collaborate with data scientists to optimize model architectures, enforce clean code standards, and transition experimental models into production-ready and scalable software. Drive Application Integration : Build robust APIs, microservices, and backend business logic required to seamlessly connect machine learning models with downstream applications and serve predictions efficiently. Build Data & Feature Pipelines : Construct and maintain scalable data pipelines and feature stores to ensure reliable, high-throughput data ingestion for both training and real-time inference. Own Production Health & Observability : Establish robust monitoring, anomaly detection, and incident response systems to track data quality, model drift, and A/B testing performance. Optimize System Performance : Troubleshoot production bottlenecks and optimize models for latency, throughput, and compute efficiency (e.g., GPU/CPU utilization and API cost management). What you’ll Need: Experience in software engineering, machine learning engineering, data science, or a related field; 2+ years of professional experience required for Senior-level candidates. Demonstrate a solid understanding of core ML concepts and frameworks, including supervised/unsupervised learning, optimization, evaluation metrics, and hands-on experience with PyTorch, TensorFlow, or Scikit-Learn. Have practical experience developing agentic AI workflows or LLM applications, including autonomous agents or orchestration frameworks like LangChain, AutoGen, CrewAI, or custom tool-calling/RAG architectures. Show strong proficiency with Python or Go in production environments, with exposure to distributed computing frameworks like Apache Spark considered a strong plus. Understand systems architecture and distributed systems deeply, with the ability to design, maintain, and scale complex ML pipelines and application logic. Experience with container orchestration tools like Kubernetes, or workflow orchestration tools like Apache Airflow, is highly desirable for managing scalable ML workloads. Bring research to reality with the proven ability to read, dissect, and practically implement advanced algorithms, papers, and methodologies from published AI/ML research. Apply a pragmatic, high-velocity engineering approach with a long-term vision, using a systematic "hacker" mindset to build clever, elegant, and resourceful solutions under tight constraints while balancing rapid delivery with sustainable, scalable practices that minimize technical debt. Be able to communicate in English and Thai both speaking and writing fluently.