AI Engineer II - Translation

Key Responsibilities

• Design, train, and deploy neural machine translation (NMT) systems for multilingual scenarios, with emphasis on low-diffusion languages.
• Optimize models for low-resource and specialized domain languages, leveraging techniques like transfer learning and few-shot adaptation.
• Collaborate with the LLM AI Engineer to integrate large language models into translation pipelines and compare approaches for different language pairs.
• Develop post-editing and quality assurance tools to augment human translators, incorporating human-in-the-loop feedback.
• Work closely with linguists, product managers, and engineers to integrate AI into translation pipelines and gather domain feedback.
• Continuously evaluate and benchmark model performance using standardized metrics (BLEU, COMET) and custom domain-specific metrics.
• Stay current with research advancements in multilingual NLP and low-resource translation techniques.

Qualifications

• Bachelor's or Master’s degree in Computer Science, Computational Linguistics, Statistics, or related field.
• Strong background in NLP and machine translation systems.
• Proven experience optimizing models for low-resource or underrepresented languages.
• Proficiency in Python and ML frameworks (PyTorch, TensorFlow, Hugging Face).
• Experience with multilingual datasets, translation quality evaluation, and human feedback incorporation.

Preferred Qualifications

• Prior work in translation, interpretation, summarization, or cross-lingual QA
• Contributions to open-source NLP projects and translation quality projects
• Experience working with speech-to-text pipelines or multimodal systems