Natural Language Processing (NLP) Engineer

Summary

OVA.Work is seeking a skilled Natural Language Processing (NLP) Engineer to design, develop, and deploy intelligent language-based AI solutions. The ideal candidate will build scalable applications for text understanding, conversational AI, and generative AI while collaborating with cross-functional teams.

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

Skills

• 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
• 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

Qualifications

Must Haves

• 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

Nice to Haves

• 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

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.