below marketmost similar roles pay hereabove market
This role pays less than
56%
of similar roles. Most pay
$202,800–$254,750
— the blue band above.
At the midpoint, this role pays about
$214k
versus about
$229k
for comparable roles.
Based on 240 similar postings.
Employer
About Apple Inc
Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software
Apple Inc currently has
3535 open roles
on FindRole.
Listed pay typically runs
$166,600–$277,600
across 2738 roles with salary data.
The AI/ML - Machine Learning Engineer, Text Language Identification joins the Multilingual Intelligence team to build next-generation systems for detecting and classifying languages across diverse scripts and regions. This role involves the full model lifecycle, including data curation, model design, evaluation, and deployment. You will design and train neural models to handle hundreds of languages, including low-resource and mixed-language scenarios. Key responsibilities include building multilingual data pipelines, developing evaluation frameworks for edge cases like code-switching, and researching transfer learning or multilingual pretraining. You will use Python, Bash, and deep learning frameworks like PyTorch, TensorFlow, or JAX, while utilizing the Hugging Face ecosystem. The work solves the technical challenge of providing accurate, robust, and efficient language identification for translation, search, and accessibility features.
What does a Machine Learning Engineer earn in California?
Median $237125 from 194 postings across 34 companies.
Design, train, and evaluate text language identification models for hundreds of languages and scripts.
Build and maintain multilingual data pipelines for collection, cleaning, and augmentation of training data.
Develop evaluation frameworks for edge cases like short text, code-switching, and noisy input.
Research and apply transfer learning and multilingual pretraining to improve coverage for underrepresented languages.
Explore lightweight model architectures and optimization strategies for efficient cloud and edge deployment.
Integrate language identification capabilities into user-facing features based on real-world performance feedback.
Contribute to best practices for model experimentation, versioning, and reproducibility.
What we're looking for
2+ years of experience in machine learning, NLP, or related fields with hands-on experience training and evaluating neural models.
Proficient programming skills in Python and at least one major deep learning framework such as PyTorch, TensorFlow, or JAX.
Bachelor's or Master's degree, or equivalent practical experience, in Computer Science, Machine Learning, Computational Linguistics, or a related technical field.
Experience working with multilingual, multi-script, or cross-lingual datasets.
Experience with text classification, language identification, dialect identification, or similar NLP tasks involving multiple languages (preferred).
Familiarity with embedding models, sentence representations, or contrastive learning methods (preferred).
Understanding of model optimization techniques such as quantization, pruning, or knowledge distillation (preferred).
Familiarity with Hugging Face ecosystem and modern NLP pipelines (preferred).