Senior Machine Learning Engineer

Senior Machine Learning Engineer

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.

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 include:

• 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.