Language Engineer

Job Title: Language EngineerLocation:RemoteJob Type:Full-TimeAbout the Role:We are seeking aLanguage Engineer with a strong expertise in Generative AIto support the development of advanced NLP systems. In this role, you will bridge the gap between linguistic insights and cutting-edge AI models, contributing to the design, evaluation, and refinement of large language models (LLMs), prompt engineering strategies, and multilingual systems. This is a collaborative role where linguistic intuition meets deep technology. You’ll work alongside machine learning scientists, applied researchers, and product engineers to shape next-gen GenAI experiences.Key Responsibilities: Design and execute linguistic experiments to evaluate and improve generative models across multiple languages and tasks. Contribute to prompt engineering, fine-tuning, and evaluation of LLMs for conversational AI, summarization, translation, and more. Curate, annotate, and manage high-quality language datasets to support model training and benchmarking. Perform linguistic error analysis and develop rule-based or data-driven corrections for model outputs. Collaborate with research teams to publish internal findings, whitepapers, or contribute to academic papers. Support multilingual and cross-cultural GenAI development by ensuring linguistic and cultural nuance in outputs. Prototype and implement linguistic modules/tools to automate analysis and annotation workflows. Monitor emerging trends in computational linguistics, foundation models, and GenAI.Required Qualifications: Proven experience working with NLP/LLM models (e.g., GPT, BERT, T5, LLaMA, Claude, Gemini). Solid understanding of syntax, semantics, discourse, and pragmatics. Strong programming/scripting skills in Python and experience with NLP libraries (e.g., spaCy, Hugging Face Transformers, NLTK). Experience in designing or executing linguistic evaluations and A/B tests for AI models. Familiarity with large-scale data annotation, QA/QC processes, and labeling tools.Preferred Qualifications: Experience in prompt engineering and GenAI evaluation techniques. Experience with multilingual or low-resource language support in NLP systems. Strong research publication record or contributions to open-source NLP/GenAI projects. Familiarity with MLOps tools, vector databases, LLMOps, and retrieval-augmented generation (RAG). Ability to interpret and distill model behaviors into actionable insights for research teams.What You’ll Get: A chance to influence GenAI experiences and multilingual LLM development at scale. Exposure to state-of-the-art AI systems, tools, and global NLP challenges. A supportive and intellectually stimulating work environment.

Created: 2025-07-23