NLP / LLM Engineer — Model Training & Fine-Tuning

• *Experience**: 2\+ years preferred

• *Skills**: Python, NLP, LLMs, Hugging Face, PyTorch

• *Job Overview**

We are looking for an NLP / LLM Engineer to develop, train, fine\-tune, and optimise machine learning models for text analysis and information extraction. The role involves improving model accuracy, evaluating performance, and building reliable AI pipelines for real\-world applications.

• *Key Responsibilities**

Develop and improve NLP models for text analysis and information extraction.

Train and fine\-tune pretrained models to improve performance.

Prepare datasets, evaluate model outputs, and analyse errors.

Experiment with different models and techniques to improve accuracy.

Build and optimise reliable NLP pipelines for production use.

• *Required Technical Skills**

Strong Python programming skills.

Good understanding of NLP and machine learning fundamentals.

Hands\-on experience with PyTorch.

Experience with Hugging Face Transformers and pretrained models.

Practical experience building and evaluating text classification models.

Experience training or fine\-tuning pretrained models.

Knowledge of dataset preparation, tokenization, and data splitting.

Understanding of overfitting, generalization, class imbalance, and model evaluation metrics.

Ability to analyse model errors and improve performance systematically.

• *Preferred Skills**

Experience with BERT, RoBERTa, DeBERTa, Qwen, Llama, or comparable models.

Experience with LoRA, QLoRA, and parameter\-efficient fine\-tuning.

Knowledge of text embeddings, semantic search, and duplicate detection.

Experience with model quantization and local model inference.

Experience with FastAPI, REST APIs, and Docker.

Familiarity with MLflow, Weights \& Biases, or other experiment\-tracking tools.

Experience deploying models on CPU or GPU infrastructure.

Pay: ₹30,000\.00 \- ₹50,000\.00 per month

Work Location: In person