Natural Language Processing Engineer

About CreditSea

CreditSea (Innotech CreditSea Platforms Pvt. Ltd.) is a digital lending platform headquartered in Raipur, Chhattisgarh, that gives individuals quick, reliable access to loans when they need funds urgently. Built on transparency, integrity, and a customer-first approach, it delivers a seamless journey from application to disbursement, using data and technology to keep every step fast and secure.

About the Role

We are looking for a hands-on NLP Engineer. You will work on problems such as document understanding for KYC and income proofs, customer support automation, text-based risk and fraud signals, and LLM-powered assistants, and take models from experiment to production.

Key Responsibilities

• Design, train, fine-tune, and evaluate NLP models for tasks such as text classification, named entity recognition, sentiment analysis, summarization, question answering, and semantic search.
• Build applications using large language models (LLMs), including prompt engineering, fine-tuning, and retrieval-augmented generation (RAG).
• Collect, clean, annotate, and preprocess large text datasets, including multilingual data (English, Hindi, and other Indian languages where relevant).
• Develop and maintain end-to-end NLP pipelines, from data ingestion to model serving.
• Deploy models as APIs or services and monitor their performance, latency, and accuracy in production.
• Run experiments, track metrics, and continuously improve model quality.
• Collaborate with product managers, backend developers, and domain experts to translate business needs into technical solutions.
• Document code, experiments, and model behavior; take part in code reviews.
• Keep up with the latest research and tools in NLP and generative AI, and recommend practical improvements.
• Build NLP solutions for fintech use cases: extracting fields from KYC, bank statement, and salary documents (OCR + NER), and classifying and summarizing customer support chats and calls.
• Develop LLM-based chat or voice assistants for customer support and collections, with guardrails for accuracy, data privacy, and compliance.
• Work with the data and risk teams to turn unstructured text into features that support credit assessment and fraud detection.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, Mathematics, Computational Linguistics, or a related field.
• About 2 years of professional experience in NLP or machine learning.
• Strong programming skills in Python.
• Hands-on experience with Hugging Face Transformers, spaCy, NLTK, and deep learning frameworks such as PyTorch or TensorFlow.
• Solid understanding of NLP fundamentals: tokenization, embeddings, transformers, attention, sequence models, and evaluation metrics (F1, BLEU, ROUGE, etc.).
• Experience working with LLMs and techniques such as prompt engineering, fine-tuning, and RAG.
• Familiarity with SQL and data handling libraries (Pandas, NumPy, scikit-learn).
• Experience with Git and basic software engineering practices.
• Good problem-solving, communication, and teamwork skills. Preferred Skills (Nice to Have)
• Experience with vector databases (FAISS, Pinecone, Chroma, Milvus) and frameworks such as LangChain or LlamaIndex.
• Experience with multilingual or Indic-language NLP (Hindi,Engilsh etc.).
• Knowledge of model deployment tools: FastAPI, Flask, Docker, and cloud platforms (AWS, GCP, or Azure).
• Familiarity with MLOps practices, including experiment tracking (MLflow, Weights & Biases) and CI/CD.
• Experience with speech-to-text, OCR, or document AI.
• Published projects, open-source contributions, or Kaggle/competition experience.
• Experience in fintech, banking, NBFC, or lending, and familiarity with KYC, credit risk, or collections workflows.

What We Offer

• Hands-on work on production-grade AI projects using real fintech and lending data.
• Learning and growth opportunities in NLP and generative AI.
• Collaborative onsite work culture in Raipur.
• Competitive salary as per industry standards and experience.
• Additional benefits as per company policy.