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Lilt

AI-powered multilingual translation platform for enterprises

AI Benchmark Engineer

Natural Language Processing & LLMsConfirmed live in the last 24 hours
ContractNo salary listed

About the Job

Requirements

  • At least 1 year of experience in software or prompt engineering.
  • Native or near-native fluency in Japanese, with a deep understanding of its grammar, register, and phrasing rules, and high English proficiency.
  • Strong proficiency in Python, standard shell scripting, and data processing.
  • Extensive experience with Terminal/CLI-based development workflows and working familiarity with coding agents.
  • Deep technical understanding of multilingual text processing pitfalls, including encoding and decoding robustness, Unicode normalization, locale-dependent conventions such as collation, casing, and non-Gregorian dates, text input/output, toolchain interoperability, and safe string operations.

Responsibilities

  • Evaluate coding agents through task engineering.
  • Build realistic task environments using datasets and files in Japanese, keeping assets in the target language.
  • Find AI failure points in Japanese through prompting and translation.
  • Support development of robust reference implementations and write reliable, deterministic verifier scripts, using rubric-based judging only when strictly necessary.
  • Analyze execution logs and calibrate task difficulty from Easy to Very Hard using standard Terminal-Bench run configurations against various model tiers.
  • Participate in a four-layer human quality-control process—creation, human review, calibration review, and audit—alongside automated LLM-based checks to ensure fairness, grammatical accuracy, and benchmark integrity.

Desired Qualifications

  • A proven track record at leading technology companies and/or graduation from top-tier engineering universities.

About the Company

Lilt

AI-powered multilingual translation platform for enterprises

Lilt provides an AI-powered translation platform for enterprises to manage multilingual content. It uses a Contextual AI Engine with a human-in-the-loop: AI translations are reviewed by professional linguists, and feedback helps the model improve. It supports 70+ languages and formats and integrates with 100+ enterprise systems, sold as a subscription SaaS (plus direct translation services). Its goal is to speed up high-volume translation while ensuring accuracy and consistency across global content.

Company size
501-1,000
Company stage
Series C
Total funding
$95.6M
Headquarters
San Francisco, CA
Founded
2015

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