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Liquid AI is seeking a scientist to enhance language and multimodal foundation models with a focus on Japanese-language use cases. The role covers the full experimental cycle from diagnosing model weaknesses to shaping data or training approaches, through evaluation and implementation, to improve model checkpoints and repeatable methods.
The position involves remote work with frequent collaboration across teams and occasional travel for cross-regional work.
Improve the capabilities and reliability of language and multimodal foundation models, with particular attention to Japanese-language use cases. The scientist owns the experimental cycle from diagnosing model weaknesses and shaping data or training approaches through evaluation and implementation, turning useful findings into improved model checkpoints and repeatable methods.
Primarily remote for candidates based in Japan, with typical visits to a Tokyo office once or twice a week. Hours are flexible, with collaboration across Japanese customers and colleagues in other time zones; travel to the United States, conferences, and occasionally within Japan is part of the role. The offer includes close collaboration with model research and engineering teams, professional development, unlimited paid time off, competitive salary, equity, and standard employee benefits in Japan.