Liquid AI

Join Liquid AI as an ML Scientist to enhance foundation models for the Japanese market, focusing on post-training strategies and experimental methodologies.

Deploy advanced language and multimodal models into reliable, efficient production systems for customers in Japan. This highly autonomous role combines hands-on ML engineering, inference optimization, evaluation, and technical customer collaboration.

Own and improve the GPU cluster infrastructure powering Liquid AI’s foundation model training and research. You’ll combine hands-on software engineering, operational response, and automation to make compute platforms more reliable and efficient.

Own the end-to-end development pipeline for an on-device audio-to-function-calling model deployed in automotive products. You’ll turn partner requirements into trained, evaluated checkpoints while working across data, fine-tuning, evaluation, and production releases.

Build Liquid AI’s solutions architecture function while taking AI customer engagements from technical discovery through go-live. You’ll create demos and proofs of concept, translate efficient models into customer outcomes, and shape product direction through field feedback.

Own end-to-end applied post-training for vision-language models, combining enterprise customer delivery with hands-on multimodal model development. You will curate data, fine-tune and align VLMs, design evaluations, and help advance Liquid AI’s core post-training stack.

Own end-to-end applied ML engagements that adapt large-scale sequential recommendation models for enterprise customers. You will build data and evaluation workflows, fine-tune models, and deliver production-focused personalization and ranking systems.

Own the applied post-training work that adapts Liquid AI’s audio language models for enterprise voice-driven function calling. You’ll build data and evaluation pipelines, fine-tune and align models, and ship real-time, on-device audio AI solutions.