AIML - Senior Machine Learning Research Engineer, LLM Post-training (Multilinguality)

The Multilingual Intelligence team is looking for a machine learning engineer to

build the next generation of text language identification systems. You will

develop models that accurately detect and classify languages across diverse

scripts, regions, and user contexts — forming the backbone of multilingual

features used by millions of people worldwide. You will work alongside a team of

world-class experts to explore novel modeling approaches, data strategies, and

evaluation methodologies that push the boundaries of what's possible in language

detection at scale. Passionate about Natural Language Processing, multilingual

systems, and building ML that works for everyone regardless of the language they

speak? Join us to make every device fluent in every language.

DESCRIPTION

Text language identification is a foundational capability that powers

multilingual experiences across products — from translation and search to

content recommendation and accessibility. As the number of supported languages

grows and user expectations rise, the challenge is building models that are not

only accurate but also fair, robust, and efficient across the full spectrum of

the world's languages. We are looking for a machine learning engineer passionate

about building high-quality, inclusive language technology. As a member of the

team, you will work across the full model lifecycle — from data curation and

model design to evaluation and deployment. You will collaborate with

researchers, engineers, and linguists to ensure our language identification

systems perform reliably for users everywhere, regardless of how they write or

what language they use. The successful candidate should be a strong team player

with excellent oral and written communication skills and a genuine passion for

building ML systems that work for the world's linguistic diversity.

MINIMUM QUALIFICATIONS

2+ year 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.

PREFERRED QUALIFICATIONS

Experience with text classification, language identification, dialect

identification, or similar NLP tasks involving multiple languages. Familiarity

with embedding models, sentence representations, or contrastive learning

methods. Understanding of model optimization techniques such as quantization,

pruning, or knowledge distillation, and a general interest in efficient

inference. Experience with low-resource languages, code-switching, or

mixed-language input handling. Familiarity with Hugging Face ecosystem

(transformers, tokenizers, datasets) and modern NLP pipelines. Ability to

formulate a problem, design experiments, and implement end-to-end solutions in

Python and Bash. Strong communication skills and a passion for working

cross-functionally across Research, Engineering, and Product teams.