Remote AI Benchmark Engineer — Native Spanish (Mexico)

Lilt

México

Remote

MXN 344.000 - 689.000

Vollzeit

14 Tage+

Eine vollständige Bewerbung in einer Minute

Maßgeschneiderter Lebenslauf und Anschreiben – versandbereit.

Schaffe es an den ATS-Filtern vorbei

Zusammenfassung

Lilt seeks experienced native-speaking software engineers to design, build, and validate multilingual benchmarks for evaluating large language models. This remote, freelance role focuses on high-signal tasks in your native language to test multilingual robustness without English translation crutches.

You will handle task engineering, asset creation, prompting, implementation and verification, calibration, and QA within a four-layer review workflow.

Qualifikationen

  • 5+ years of industry experience in software engineering.
  • Proven track record at leading technology companies or top-tier universities.
  • Native or near-native fluency in the target language with high English proficiency.
  • Strong Python, shell scripting, and data processing skills.
  • Extensive experience with Terminal/CLI workflows and coding agents.
  • Deep understanding of multilingual text processing pitfalls (Unicode, locale rules, I/O).

Aufgaben

  • Task Engineering: Evaluating Coding Agents.
  • Asset Creation: Build native-language task environments with data and files in your language.
  • Prompting & Translation: identify failure points in your language.
  • Implementation & Verification: develop robust solutions and deterministic verifier scripts.
  • Calibration & Execution: analyze logs and calibrate task difficulty across model tiers.
  • Quality Assurance: participate in 4-layer quality control and automated checks.

Kenntnisse

Python
Shell scripting
Data processing
Terminal/CLI workflows
Coding agents
Native language fluency
English proficiency

Ausbildung

Graduation from top-tier engineering universities

Jobbeschreibung

Lilt seeks experienced native-speaking software engineers to design, build, and validate multilingual benchmarks for evaluating large language models. This remote, freelance role focuses on high-signal tasks in your native language to test multilingual robustness without English translation crutches.

You will handle task engineering, asset creation, prompting, implementation and verification, calibration, and QA within a four-layer review workflow.

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