About the Company

Our client is a stealth AI startup backed by one of Southeast Asia's leading technology companies and is currently building its global founding team.

The company is developing an AI-native communication platform designed to simplify everyday tasks by integrating AI directly into conversations. Instead of switching between multiple applications, users can plan, organize, compare, research, and complete tasks within a single intelligent assistant.

Serving a market of billions of users still relying on traditional productivity tools, the platform focuses on delivering reliable AI workflows, persistent context, multi-step reasoning, and seamless task execution. The mission is to create an AI assistant that significantly improves productivity while making everyday work simpler and more intuitive.

About the Role

Our client is seeking a Senior Machine Learning Engineer to design and build production-grade machine learning systems that power its AI platform. This is a hands-on technical role focused on solving complex machine learning challenges, translating research into scalable solutions, and delivering reliable AI systems that operate effectively in real-world environments.

Working closely with research, product, and engineering teams, this position will independently own critical machine learning components from development through production deployment.

Key Responsibilities

• Build and develop core machine learning systems that power AI-driven product capabilities.
• Own the end-to-end machine learning lifecycle, including data preparation, model training, evaluation, inference, deployment, and continuous iteration.
• Translate research concepts into reliable, production-ready machine learning solutions.
• Investigate and resolve model performance issues and production system failures using real-world operational insights.
• Continuously improve machine learning systems through rapid experimentation, measurement, and iteration.
• Collaborate closely with research, product, and engineering teams to deliver impactful AI features.
• Provide technical guidance through code reviews, best practices, and mentorship of fellow machine learning engineers.
• Develop solutions that balance real-world production requirements, including latency, scalability, cost efficiency, reliability, and safety.

Requirements

• Proven experience building and deploying production machine learning systems used by real users.
• Strong understanding of modern machine learning models, including their behavior, limitations, and failure modes in production environments.