ML Engineer - Multilingual Text Identification & NLP

Apple Inc.

Cupertino (CA)

On-site

USD 150,000 - 278,000

Full time

14 days+

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Benefits offered by this job

Stock programs
Discretionary bonuses
Relocation assistance

Job summary

Apple Inc. in Cupertino, CA seeks an AI/ML Engineer for text language identification. You will design and train models across languages, build multilingual data pipelines, and evaluate edge cases like code-switching and low-resource languages.

You will collaborate with researchers and engineers, exploring transfer learning and efficient inference for device and cloud deployment. Proficiency in Python and DL frameworks is required; Hugging Face experience is a plus.

Qualifications

  • 2+ years in ML/NLP with hands-on training and evaluation of neural models.
  • Proficient in Python and at least one major DL framework (PyTorch, TensorFlow, or JAX).
  • Bachelor's or Master's in CS/ML/Computational Linguistics or related technical field.
  • Experience with multilingual, multi-script, or cross-lingual datasets.

Responsibilities

  • Design, train, and evaluate text language identification models across hundreds of languages, scripts, and locales.
  • Build and maintain multilingual data pipelines for collecting, cleaning, and curating training data.
  • Develop evaluation frameworks that cover short text, code-switching, transliteration, noisy input, and near-identical language pairs.
  • Collaborate with product and engineering teams to integrate language identification into user-facing features.

Skills

Machine learning
NLP
Python

Education

Bachelor's or Master's in CS/ML/Computational Linguistics

Tools

PyTorch
TensorFlow
JAX
Hugging Face

Job description

Apple Inc. in Cupertino, CA seeks an AI/ML Engineer for text language identification. You will design and train models across languages, build multilingual data pipelines, and evaluate edge cases like code-switching and low-resource languages.

You will collaborate with researchers and engineers, exploring transfer learning and efficient inference for device and cloud deployment. Proficiency in Python and DL frameworks is required; Hugging Face experience is a plus.

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