Natural Language Processing Specialist

6 days ago

Singapore RiceBowl Full time
Job Summary:

RiceBowl is seeking a highly skilled Natural Language Processing Engineer to join our team. As a key member of our organization, you will be responsible for developing and implementing advanced language models to enhance our capabilities in understanding, processing, and generating human language.

Key Responsibilities:
  • Design, build, and implement NLP models and algorithms for tasks such as text classification, sentiment analysis, named entity recognition, language translation, and question-answering systems.
  • Develop pipelines for data cleaning, tokenization, lemmatization, and vectorization to preprocess large volumes of unstructured text data.
  • Identify and engineer relevant features from text data to improve model performance.
  • Train, fine-tune, and evaluate NLP models using frameworks like Hugging Face Transformers, TensorFlow, or PyTorch.
  • Collaborate with data scientists, software developers, and product teams to integrate NLP models into applications and services.
  • Stay current with advancements in NLP research, such as large language models (e.g., GPT, BERT), and apply new methods to improve existing products.
  • Deploy and maintain NLP models in production environments, ensuring scalability, performance, and reliability.
  • Monitor the performance of deployed models, performing updates and retraining as necessary to ensure continued effectiveness.
  • Document the development processes, code, models, and outcomes for future reference and reproducibility.
Qualifications:
  • Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Linguistics, or a related field.
  • 2+ years of experience in natural language processing, machine learning, or a related field.
  • Hands-on experience with NLP libraries and frameworks such as Hugging Face Transformers, spaCy, NLTK, or Gensim.
  • Experience with machine learning frameworks like TensorFlow or PyTorch.
  • Proficiency in programming languages such as Python or R.
  • Familiarity with deep learning techniques for NLP, such as attention mechanisms and transformer models.
  • Strong understanding of NLP tasks (e.g., text classification, named entity recognition, machine translation).
  • Knowledge of traditional machine learning algorithms (e.g., SVM, Naive Bayes) and modern deep learning models (e.g., RNNs, LSTMs, BERT, GPT).
  • Experience with cloud platforms (AWS, GCP, or Azure) for deploying and scaling NLP models.
  • Strong problem-solving skills and ability to work on complex projects with minimal guidance.
  • Ability to communicate technical concepts clearly to both technical and non-technical stakeholders.
Preferred Qualifications:
  • Experience with large-scale language models (e.g., BERT, GPT) and transfer learning in NLP.
  • Familiarity with distributed computing and big data technologies like Spark or Hadoop.
  • Experience with MLOps practices and tools for deploying and monitoring machine learning models.
  • Familiarity with tools such as Docker, Kubernetes, and CI/CD pipelines.
  • Knowledge of multilingual NLP models and their application in global contexts.

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