Natural Language Processing (NLP) EngineerJob Title Natural Language Processing (NLP) Engineer
Job Summary We are seeking a skilled Natural Language Processing (NLP) Engineer to design, develop, and deploy intelligent language-based AI solutions. The ideal candidate will have expertise in NLP, deep learning, transformer models, and Large Language Models (LLMs). You will build scalable applications for text understanding, conversational AI, information extraction, document processing, search, and generative AI while collaborating with cross-functional teams to deliver production-ready AI solutions.
Key Responsibilities - Design, develop, and deploy NLP and Generative AI solutions for real-world applications.
- Build and optimize models for text classification, named entity recognition (NER), sentiment analysis, question answering, summarization, machine translation, text generation, and conversational AI.
- Develop and fine-tune transformer-based models such as BERT, RoBERTa, T5, GPT, Llama, Mistral, and Gemma.
- Build Retrieval-Augmented Generation (RAG) pipelines using embeddings, vector databases, and retrieval frameworks.
- Perform data preprocessing, tokenization, feature engineering, model training, evaluation, and optimization.
- Develop scalable APIs and inference services for NLP applications.
- Evaluate model performance using NLP metrics such as Precision, Recall, F1-Score, BLEU, ROUGE, METEOR, and BERTScore.
- Collaborate with data scientists, ML engineers, software developers, and product teams to deploy AI solutions into production.
- Optimize model performance, latency, scalability, and inference costs.
- Stay updated with the latest advancements in NLP, LLMs, Generative AI, and agentic AI.
Required Qualifications - Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Computational Linguistics, Data Science, or a related field.
- 2-5 years of experience in NLP, machine learning, or AI application development.
- Strong understanding of:
- Natural Language Processing (NLP)
- Deep Learning
- Transformer Architectures
- Language Modeling
- Information Retrieval
- Embeddings
- Prompt Engineering
- Proficiency in Python.
- Experience with PyTorch or TensorFlow.
- Hands-on experience with Hugging Face Transformers, spaCy, NLTK, or Sentence Transformers.
- Experience developing REST APIs and deploying machine learning models.
- Familiarity with Git, Docker, Linux, and SQL.
Preferred Qualifications - Experience working with Large Language Models (LLMs) such as GPT, Llama, Mistral, Gemma, Claude, or similar models.
- Hands-on experience with Retrieval-Augmented Generation (RAG), semantic search, and vector databases such as FAISS, Pinecone, Milvus, Weaviate, or Chroma.
- Familiarity with AI orchestration frameworks such as LangChain, LangGraph, or LlamaIndex.
- Experience with parameter-efficient fine-tuning (PEFT), LoRA, or QLoRA.
- Knowledge of model deployment, inference optimization, and MLOps tools such as MLflow, Kubeflow, or Docker.
- Experience with cloud platforms such as AWS, Azure, or Google Cloud.
Technical Skills - Python
- PyTorch / TensorFlow
- Hugging Face Transformers
- spaCy
- NLTK
- Sentence Transformers
- LangChain / LangGraph / LlamaIndex
- FAISS / Pinecone / Milvus / Weaviate / Chroma
- Docker
- Git
- Linux
- SQL
- REST APIs
- MLflow
- AWS / Azure / Google Cloud
Soft Skills - Strong analytical and problem-solving skills.
- Excellent communication and collaboration abilities.
- Attention to detail and commitment to building high-quality AI solutions.
- Ability to work in cross-functional and Agile teams.
- Curiosity and passion for learning emerging AI technologies.
Nice to Have - Experience with multimodal AI and vision-language models.
- Familiarity with Reinforcement Learning from Human Feedback (RLHF) or preference optimization techniques.
- Knowledge of AI agents, function calling, and workflow automation.
- Experience contributing to open-source NLP or AI projects.
- Publications or presentations related to NLP, LLMs, or Generative AI.
Benefits - Competitive salary and performance-based incentives.
- Comprehensive health and wellness benefits.
- Flexible or hybrid work arrangements.
- Learning, certification, and conference sponsorship opportunities.
- Access to modern GPU infrastructure and AI development tools.
- Opportunity to work on cutting-edge NLP, LLM, and Generative AI solutions in a collaborative and innovative environment.
