Natural Language Processing Engineer Job Description Template

Use this Natural Language Processing Engineer job description template to advertise the open roles for free using Longlist.io. You can use this template as a starting point, modify the requirements according the needs of your organization or the client you are hiring for.

Natural Language Processing Engineer Job Description Template

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Job Brief

We are looking for a Natural Language Processing Engineer to help us improve our NLP products and create new NLP applications.

NLP Engineer responsibilities include transforming natural language data into useful features using NLP techniques to feed classification algorithms. To succeed in this role, you should possess outstanding skills in statistical analysis, machine learning methods and text representation techniques.

Your ultimate goal is to develop efficient self-learning NLP applications.

Responsibilities

  • Study and transform data science prototypes
  • Design NLP applications
  • Select appropriate annotated datasets for Supervised Learning methods
  • Use effective text representations to transform natural language into useful features
  • Find and implement the right algorithms and tools for NLP tasks
  • Develop NLP systems according to requirements
  • Train the developed model and run evaluation experiments
  • Perform statistical analysis of results and refine models
  • Extend ML libraries and frameworks to apply in NLP tasks
  • Remain updated in the rapidly changing field of machine learning

Requirements

  • Proven experience as an NLP Engineer or similar role
  • Understanding of NLP techniques for text representation, semantic extraction techniques, data structures and modeling
  • Ability to effectively design software architecture
  • Deep understanding of text representation techniques (such as n-grams, bag of words, sentiment analysis etc), statistics and classification algorithms
  • Knowledge of Python, Java and R
  • Ability to write robust and testable code
  • Experience with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)
  • Strong communication skills
  • An analytical mind with problem-solving abilities
  • Degree in Computer Science, Mathematics, Computational Linguistics or similar field

What does Natural Language Processing Engineer do?

A Natural Language Processing (NLP) Engineer is responsible for developing and implementing algorithms, models, and systems that enable computers to understand and process human language. On a day-to-day basis, an NLP Engineer may perform tasks such as:

  1. Data preprocessing: Cleaning and preparing textual data for further analysis by removing noise, formatting text, and handling special characters.

  2. Language modeling: Developing statistical or machine learning models to understand the structure and patterns of natural language. This involves tasks like building n-grams, hidden Markov models, or recurrent neural networks.

  3. Named entity recognition: Designing and implementing algorithms to identify and extract entities such as names of people, organizations, locations, etc., from text.

  4. Sentiment analysis: Creating models that determine the sentiment (positive, negative, neutral) expressed in text or social media posts.

  5. Text classification: Building algorithms that automatically categorize and classify text into predefined categories, such as spam detection, topic classification, or sentiment analysis.

  6. Machine translation: Developing models or systems for translating text from one language to another using techniques such as statistical machine translation or neural machine translation.

  7. Speech recognition: Creating algorithms or systems that convert spoken language into written text by using techniques like acoustic modeling, language modeling, and deep learning.

  8. Chatbot development: Designing and implementing conversational agents or virtual assistants that can understand and respond to human language queries using techniques like intent recognition and response generation.

  9. Evaluating and improving models: Analyzing the performance of NLP models by conducting experiments, measuring accuracy, precision, and recall, and fine-tuning the models to achieve better results.

  10. Research and staying up-to-date: Keeping up with the latest research in NLP by reading academic papers, attending conferences, and participating in online forums and communities.

Note that the specific tasks and responsibilities of an NLP Engineer may vary based on the organization, project requirements, and individual expertise.

Natural Language Processing Engineer Job Description Examples

Nlp Core Technology, Ml Engineer - Safety Ai• Apple

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Natural Language Processing Engineer• Turing Talent

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Natural Language Processing Engineer• Tietronix

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Software Engineer - Natural Language Processing• Josh.ai

Job Overview:

Josh.ai is searching for a team player who is passionate about tackling some of the most challenging problems in natural language processing. This position works closely with our CTO on our natural language processing strategy, which has an immediate impact on the Josh customer experience and our ability to bring joy to our customers’ homes...

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