Member of Technical Staff - ML Scientist, Japanese Multimodal

Liquid AI

United States

Hybrid

USD 180,000 - 250,000

Full time

7 days ago
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Benefits offered by this job

Unlimited paid time off
Equity
Employee benefits in Japan
Professional development

Job summary

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.

Qualifications

  • Strong experimental practice: formulate hypotheses, establish baselines, design informative ablations, and use evidence to guide follow-up work.
  • Ability to identify training-data gaps and devise curation, filtering, generation, and supervision strategies.
  • Comfort owning the full post-training loop, from datasets and training to evaluation, error analysis, and implementation.
  • Rigor in making experiments reproducible and conclusions well supported, with successful research ready for integration into shared systems.
  • Clear communication and effective collaboration with research, engineering, and applied teams working across locations.

Responsibilities

  • Design and run post-training work such as supervised fine-tuning, preference optimization, reinforcement learning, and distillation.
  • Curate training data using human, synthetic, and model-generated signals, focusing on Japanese and domain-specific capabilities.
  • Build evaluations that reveal capability and reliability gaps across Japanese and broader use cases.
  • Analyze errors and use findings to refine data mixtures, objectives, and training methods.
  • Run controlled experiments at increasing scale, document evidence, and translate results into technical decisions and reusable workflows.

Job description

Role overview

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.

Responsibilities
  • Design and run post-training work such as supervised fine-tuning, preference optimization, reinforcement learning, and distillation.
  • Curate training data using human, synthetic, and model-generated signals, focusing on Japanese and domain-specific capabilities.
  • Build evaluations that reveal capability and reliability gaps across Japanese and broader use cases.
  • Analyze errors and use findings to refine data mixtures, objectives, and training methods.
  • Run controlled experiments at increasing scale, document evidence, and translate results into technical decisions and reusable workflows.
Requirements
  • Strong experimental practice: formulate hypotheses, establish baselines, design informative ablations, and use evidence to guide follow-up work.
  • Ability to identify training-data gaps and devise curation, filtering, generation, and supervision strategies.
  • Comfort owning the full post-training loop, from datasets and training to evaluation, error analysis, and implementation.
  • Rigor in making experiments reproducible and conclusions well supported, with successful research ready for integration into shared systems.
  • Clear communication and effective collaboration with research, engineering, and applied teams working across locations.
Benefits and work setup

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.

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