NLP Engineer

Role Overview

Key Responsibilities

• Lead scalable NLP and LLM-powered solution development.
• Architect and optimize RAG pipelines, embeddings, vector search, and LLM applications.
• Fine-tune and evaluate transformer-based models and LLMs for production.
• Build data, training, inference, and model-evaluation pipelines.
• Improve model quality, latency, scalability, reliability, and cost.
• Establish practices for AI experimentation, deployment, evaluation, and monitoring.
• Translate business requirements into AI/ML solutions and collaborate with technical and product stakeholders.
• Mentor engineers and provide technical leadership across NLP and Generative AI initiatives.

Requirements

• 5+ years of professional experience in NLP, machine learning, or Generative AI.
• Strong Python programming and hands-on experience with PyTorch, TensorFlow, Hugging Face, or equivalent frameworks.
• Deep understanding of NLP, transformers, LLMs, embeddings, RAG, fine-tuning, and model evaluation.
• Experience taking AI/ML solutions from experimentation to production.