ML Engineer: Text Language Identification for Global Reach

Apple, Inc.; Cupertino (CA); Presencial; USD 150 000 - 278 000; Tempo integral

Vantagens oferecidas por esta oferta de emprego

Comprehensive medical and dental cover

Retirement benefits

Discounted products and services

Tuition reimbursement

Resumo da oferta

Apple, Inc. in Cupertino, CA is seeking an AI/ML Engineer to build next-generation text language identification systems. You will design models across hundreds of languages and deploy them at scale, collaborating with researchers, engineers, and linguists.

You will work on data curation, model design, and evaluation, employing transfer learning and data augmentation to improve coverage for underrepresented languages and ensuring efficient inference on diverse devices.

Qualificações

• 2+ years of experience in ML/NLP with hands-on training/evaluation of neural models.
• Proficiency in Python and a major DL framework (PyTorch, TensorFlow, or JAX).
• BS/MS or equivalent in CS/ML/Computational Linguistics or related field.
• Experience with multilingual, multi-script, or cross-lingual datasets.

Responsabilidades

• Design, train, and evaluate text language identification models across languages and scripts.
• Build multilingual data pipelines for diverse language sources.
• Develop evaluation frameworks, including edge cases like code-switching and short text.
• Collaborate with product and engineering teams to integrate language identification features.
• Research transfer learning and data augmentation to improve coverage of underrepresented languages.
• Explore lightweight architectures for device- and cloud-friendly deployment.
• Contribute to model experimentation, versioning, and reproducibility practices.

Conhecimentos

ML/NLP

Python

DL frameworks

Formação académica

BSc/MSc in CS/ML/Computational Linguistics

Ferramentas

Hugging Face

Bash

Descrição da oferta de emprego

Apple, Inc. in Cupertino, CA is seeking an AI/ML Engineer to build next-generation text language identification systems. You will design models across hundreds of languages and deploy them at scale, collaborating with researchers, engineers, and linguists.

You will work on data curation, model design, and evaluation, employing transfer learning and data augmentation to improve coverage for underrepresented languages and ensuring efficient inference on diverse devices.