Bangkok
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Listing record updated: October 20, 2026. We archive records after 60 days without an update. This date does not confirm that the employer is still hiring.
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Senior individual contributor role leading the design and improvement of machine learning-powered solutions in a production environment. The position focuses on complex user-facing AI systems, driving experimentation and model improvement, and collaborating with cross-functional teams to turn ambiguous problems into scalable solutions.
The role requires proven experience as a Staff Data Scientist, Applied Scientist, or ML Engineer with end-to-end ownership of ML or LLM initiatives. Candidates need strong hands-on experience with ML platforms in production, solid fundamentals in machine learning and statistics, and the ability to communicate complex technical ideas to diverse stakeholders. An advanced degree in a quantitative discipline is preferred.
Lead the development and enhancement of machine learning-based solutions for complex, real-world use cases
Translate open-ended product or user problems into clear data science approaches, experiments, and deliverable outcomes
Design, test, and refine prompts, retrieval strategies, evaluation frameworks, and model behaviors to improve quality and reliability
Build robust experimentation methods to assess model performance and compare alternative approaches
Work closely with product, engineering, analytics, and other technical teams to define priorities and drive implementation
Proven experience in a Staff Data Scientist, Applied Scientist, ML Engineer, or similar role, with strong ownership of end-to-end ML or LLM initiatives
Strong hands-on experience with machine learning platforms in production settings, including experimentation, evaluation, iteration, and quality improvement
Solid background in machine learning, statistics, and data science fundamentals
Strong coding ability and practical experience working closely with software engineering teams in production environments
Advanced degree in a relevant field such as Computer Science, Machine Learning, Statistics, Mathematics, Engineering, or a related quantitative discipline is preferred
Experience building or improving systems that involve prompt design, retrieval, ranking, response quality assessment, or model evaluation
Experience operating in fast-paced, product-driven environments with high expectations for quality and execution
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