We are looking for a Text and NLP Engineer passionate about building intelligent text systems — from grammar correction to conversational AI.
This role is key to improving the quality, fluency, and human-likeness of text-based interactions with users.
Responsibilities:
- Design and build text normalization, spelling correction, and grammar checking systems and Summarization.
- Develop and maintain chatbots and conversational assistants with natural and context-aware dialogue.
- Design and author chatbot dialogue flows, fallback strategies, and personality tuning.
- Build and manage custom text datasets for fine-tuning and evaluation — dataset creation is part of the job.
- Research and apply Transformer-based and LLM models (BERT, GPT, T5, Llama, Mistral, etc.).
- Implement intent detection, entity extraction, and context tracking for interactive responses.
- Integrate NLP models with frontend and backend services via FastAPI.
- Quantize, optimize, and deploy text models on production servers for low-latency performance.
- Containerize models with Docker and manage environments with Kubernetes.
- Work closely with the speech AI team to create voice-enabled, multimodal chat experiences.
- Monitor model quality, gather real-world feedback, and continuously refine conversational accuracy.
Required Skills & Experience:
- Strong Python background and familiarity with NLP frameworks:
- HuggingFace Transformers, SpaCy, NLTK, Scikit-learn
- Experience in spell correction, intent classification, sentiment analysis, or dialogue systems.
- Familiarity with LLMs and prompt-engineering for chat-style applications.
- Proficiency with FastAPI, Docker, and Kubernetes for model deployment.
- Knowledge of quantization, distillation, or model compression techniques.
- Experience working with Persian and English text datasets is a plus.
- Understanding of MLOps, pipelines, and real-time API monitoring tools.
Nice to Have
- Experience integrating NLP and ASR systems for hybrid voice–text chatbots.