Job Description
Job description
Job Title: Language Engineer
Location: Remote
Job Type: Full-Time
About the Role:
We are seeking a Language Engineer with a strong expertise in Generative AI to 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.
