Artificial Intelligence and Machine Learning Engineer (Mid-Senior) - #1124399

About Us

iHub Solutions is a leading Log-Tech provider with a regional presence in Singapore, Kuala Lumpur, Hong Kong, Philippines, and Bangkok. We meet the complex supply chain needs of today's digital economy by integrating unique IT infrastructures, deep data analytics, and ecommerce connectivity into our business processes. With an online dashboard system driven by comprehensive process workflows (ISO 9001 standards), we offer clients the ability to track daily service performance at any time, any place. To learn more about us, visit our website at ihubsolutions.com

Job Description

We are looking for a talented and hands-on AI/ML Engineer to join our team as a key technical partner. This is a high-impact role that goes beyond just building models. You will partner closely with our in-house teams to evolve and scale our production ML infrastructure, bridge the gap between our models and our core business systems, and get solutions deployed to drive real-world value.

This is an environment where you will be hands-on with code, own the MLOps lifecycle, and act as a key role in solving our company's most complex challenges.

Responsibilities

• Own the Production ML Lifecycle: Design, build, deploy, and monitor end-to-end machine learning models.

• Build for Integration: Own the technical integration of ML models with existing systems, building and scaling robust, production-ready services (e.g. APIs).

• Act as a Senior Technical Partner: Develop project strategy, conduct mutual code reviews, and establish best practices for production-grade code.

• Cross-Functional Collaboration: Work closely with IT, Operations, and other teams to define clear technical requirements, manage dependencies, and deliver integrated solutions.

• Solve High-Value Problems:

1. Develop and implement machine learning models to improve customer satisfaction, operational efficiency, and profitability.

2. Collect, clean, and build robust data pipelines for model training.

3. Evaluate the performance of models in production and establish monitoring for data and model drift.

Qualifications

• Bachelor's degree in computer science, data science, or a related field.

• 3+ years of hands-on experience in machine learning and/or software engineering, with a proven track record of deploying and maintaining ML models in production.

• Excellent programming skills in Python and strong proficiency in SQL.

• Hands-on experience building and deploying APIs (e.g., FastAPI, Flask) and using Docker.

• Good understanding of MLOps tools (e.g., MLflow, GitLab CI) and cloud platforms (AWS, GCP, Azure).

• Experience working with large datasets.

• Strong communication and teamwork skills.

• Resourceful, curious, and able to solve problems creatively and efficiently.

Preferred Qualifications (Good-to-Have)

• Direct experience with FastAPI is a major plus.

• Experience with Generative AI (GenAI), LLMs, and frameworks like LangChain or LlamaIndex.

• Broader DevOps/Infrastructure-as-Code skills (e.g., Kubernetes, Terraform).

• Experience in the logistics, supply chain, or manufacturing industry.