Job Summary:
We are seeking a skilled NLP Engineer to join our AI and data science team. The ideal candidate will have expertise in natural language processing, machine learning, and deep learning techniques to develop intelligent systems that analyze and understand human language. You will work on building, fine-tuning, and deploying NLP models for various applications, such as chatbots, sentiment analysis, speech recognition, and text generation.
Key Responsibilities:
- Design, develop, and optimize NLP models for various use cases like text classification, entity recognition, summarization, and machine translation.
- Implement and fine-tune large language models (LLMs) using frameworks like TensorFlow, PyTorch, or Hugging Face Transformers.
- Preprocess and clean text data using techniques such as tokenization, stemming, and lemmatization.
- Build and deploy AI-powered chatbots and virtual assistants using NLP techniques.
- Work with Named Entity Recognition (NER), Part-of-Speech (POS) tagging, sentiment analysis, topic modeling, and other text-processing tasks.
- Integrate NLP models into applications and optimize them for performance and scalability.
- Conduct A/B testing and evaluate NLP models using metrics like BLEU, ROUGE, perplexity, and F1-score.
- Collaborate with data scientists, software engineers, and product teams to deploy NLP solutions.
- Stay updated with the latest research in NLP, AI, and deep learning.
Required Skills & Qualifications:
- Bachelor’s/Master’s/Ph.D. in Computer Science, AI, Data Science, or a related field.
- Strong experience with Python and NLP libraries like spaCy, NLTK, Hugging Face, Gensim.
- Proficiency in machine learning frameworks (TensorFlow, PyTorch, Scikit-learn).
- Experience with Transformer models (BERT, GPT, T5, LLaMA).
- Familiarity with vectorization techniques (Word2Vec, FastText, TF-IDF, BPE).
- Strong understanding of linguistics, semantics, and syntax.
- Experience with cloud platforms like AWS, GCP, or Azure for model deployment.
- Proficiency in using SQL and NoSQL databases for handling large text datasets.
- Experience with APIs and deploying NLP models in production environments.
- Excellent problem-solving skills and the ability to work in a team.
Preferred Qualifications:
- Experience with speech-to-text and text-to-speech applications.
- Knowledge of LLMs fine-tuning and prompt engineering.
- Hands-on experience with MLOps for model monitoring and deployment.
- Familiarity with knowledge graphs and semantic search.
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