Linguist

Key Responsibilities

• Build NLP pipelines for classification, tokenization, and retrieval-augmented generation (RAG).
• Design scalable text analytics workflows for multilingual corpora.
• Implement and fine-tune models (Hugging Face, PyTorch, fastText).
• Develop evaluation frameworks for model performance.
• Integrate NLP solutions into broader AI/search pipelines.
• Collaborate with researchers and engineers to deliver production-grade systems.

Ideal Candidate

• Degree/background in computer science, computational linguistics, or related field.
• Proficient with Hugging Face Transformers, spaCy, tokenizers, PyTorch.
• Experienced with JSON/JSONL and building scalable data pipelines.
• Strong understanding of NLP tasks: classification, tokenization, entity recognition, retrieval.
• Skilled in preprocessing, embeddings, and model fine-tuning.
• Comfortable with multilingual datasets and evaluation benchmarks.
• Interested in RAG systems and neural search pipelines.

Primary Goal

• Deliver robust NLP pipelines for classification, tokenization, and RAG at scale.

Why Join

• Work on cutting-edge RAG and NLP pipelines.
• Use state-of-the-art NLP and IR tools.
• Contribute to global, multilingual AI systems.

Operate at the intersection of AI, language, and scalable engineering.