Member of Technical Staff - Applied ML, Japanese Multimodal

Liquid AI
Tokyo
Workplace: HybridFull timeFunction: Solutions Engineering & Sales EngineeringSkills: ["Technical collaboration","Communication","Engineering judgment","Problem decomposition","Rigorous evaluation"]

Own applied ML projects for customers in Japan, taking solutions from technical discovery and scoping through production deployment. Integrate, profile, and optimize model inference to meet real constraints like latency, throughput, memory, power, cost, and reliability. Build surrounding software (pipelines, evaluation, serving, reference implementations), fine-tune or post-train when needed, and lead rigorous evaluation and error analysis while collaborating with customers and global teams.

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FursaFursa
Liquid AI
Liquid AI
1 month ago

Member of Technical Staff - Applied ML, Japanese Multimodal

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 13 hours agoStatus: Live

Job Summary

Own applied ML projects for customers in Japan, taking solutions from technical discovery and scoping through production deployment. Integrate, profile, and optimize model inference to meet real constraints like latency, throughput, memory, power, cost, and reliability. Build surrounding software (pipelines, evaluation, serving, reference implementations), fine-tune or post-train when needed, and lead rigorous evaluation and error analysis while collaborating with customers and global teams.
Location: Tokyo
Workplace: Hybrid
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering
Seniority: Mid level

Key Responsibilities

  • •Own applied ML projects for Japan customers end to end, from technical discovery and scoping through production deployment.
  • •Integrate, profile, and optimize model inference to meet requirements for latency, throughput, memory, power, cost, and reliability.
  • •Build the supporting software to turn models into product-ready capabilities (data pipelines, evaluation systems, serving components, reference implementations).
  • •Fine-tune or post-train models when needed and iterate across data, models, inference, and system design.
  • •Work with customer engineering teams during design, integration, testing, and rollout, including occasional on-site work, and convert learnings into reusable tooling.
Travel: Low travel

Pay and Benefits

Perks:Paid LeaveEquity

Key Requirements

  • •Strong engineering skills building, testing, and shipping production-quality ML systems.
  • •Hands-on deployment experience with modern language models or multimodal deep learning systems beyond notebook/API prototypes.
  • •Experience with model serving, performance profiling, or inference optimization, with judgment to balance quality and system constraints.
  • •Proficiency with the open-source ML ecosystem and designing evaluations to analyze failures and drive measurable improvements.
  • •Comfort leading technical discussions with customers and translating ambiguous requirements into shipped systems, with professional English proficiency.
Skills:Technical collaborationCommunicationEngineering judgmentProblem decompositionRigorous evaluation
Languages:EnglishJapanese
Tech Stack:VLLMSGLangLlama.cppONNX RuntimeMLXSupervised fine-tuningParameter-efficient fine-tuningPreference optimizationQuantization

Company Brief

Liquid AI
Builds AI infrastructure and tooling to enable real-time, distributed machine learning and orchestration across edge and cloud environments, simplifying deployment and management of intelligent applications.
Industry: AI & Machine Learning
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