Natural Language Process Engineer Job Description Template

A natural language process engineer, also known as NLP engineer, works and develops NLP applications using effective text representation techniques and algorithms. The main responsibilities of the engineer are to study and transform data science prototypes to design NLP applications and extend machine learning libraries.

Natural Language Process Engineer Job Description Template

A natural language process engineer, also known as NLP engineer, works and develops NLP applications using effective text representation techniques and algorithms. The main responsibilities of the engineer are to study and transform data science prototypes to design NLP applications and extend machine learning libraries.

What does a Natural Language Process Engineer do?

  • Designing and developing NLP applications
  • Using effective text representation techniques and classification algorithms
  • Training and evaluating models

Natural Language Process Engineer job summary 

  • 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

Natural Language Process Engineer responsibilities and duties

  • 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

Natural Language Process Engineer qualifications and skills

  • 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, a 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 sci-kit-learn)
  • Strong communication skills
  • An analytical mind with problem-solving abilities
  • Degree in Computer Science, Mathematics, Computational Linguistics or similar field

Alternate Job Titles

  • NLP Engineer
  • Deep Learning Engineer
  • Data Scientist

Associated Job Keywords

  • Python
  • Java
  • Machine learning
  • Algorithms
  • Statistics
  • Natural language processing
  • Data Science
  • Classification
  • Computational linguistics
  • Sentiment Analysis
  • Statistical Analysis
  • Data Structures
  • Training
  • Processing
  • R
  • Machine learning frameworks
  • Big Data
  • Reinforcement learning

Boolean Search String for Recruiters

((“statistics” OR “ml” OR “machine learning” OR “data structures” OR “data structure” OR “data science” OR “nlp” OR “natural language processing” OR “processing” ) AND (“algorithms” OR “classification” OR “computational linguistics” OR “mathematics” OR “training” ) AND (“python” OR “java” OR “r” OR “analysis” OR “sentiment analysis” OR “statistical analysis” ) )

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Our Hyper-automation platform allows you to screen candidates, complete role-fit assessments, manage interviews, and provide real-time recruitment insights (analytics). LitmusBlox offers extremely powerful yet easy to use tools to attract, engage, and hire candidates at scale.

As a matter of fact, LitmusBlox can help you reduce the number of interviews by 50% and overall effort by up to 70% to hire the top talent.

What does a Natural Language Process Engineer do?

  • Designing and developing NLP applications
  • Using effective text representation techniques and classification algorithms
  • Training and evaluating models

Natural Language Process Engineer job summary 

  • 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

Natural Language Process Engineer responsibilities and duties

  • 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

Natural Language Process Engineer qualifications and skills

  • 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, a 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 sci-kit-learn)
  • Strong communication skills
  • An analytical mind with problem-solving abilities
  • Degree in Computer Science, Mathematics, Computational Linguistics or similar field

Alternate Job Titles

  • NLP Engineer
  • Deep Learning Engineer
  • Data Scientist

Associated Job Keywords

  • Python
  • Java
  • Machine learning
  • Algorithms
  • Statistics
  • Natural language processing
  • Data Science
  • Classification
  • Computational linguistics
  • Sentiment Analysis
  • Statistical Analysis
  • Data Structures
  • Training
  • Processing
  • R
  • Machine learning frameworks
  • Big Data
  • Reinforcement learning

Boolean Search String for Recruiters

((“statistics” OR “ml” OR “machine learning” OR “data structures” OR “data structure” OR “data science” OR “nlp” OR “natural language processing” OR “processing” ) AND (“algorithms” OR “classification” OR “computational linguistics” OR “mathematics” OR “training” ) AND (“python” OR “java” OR “r” OR “analysis” OR “sentiment analysis” OR “statistical analysis” ) )

Find the best NLP engineer with LitmusBlox. Our powerful top-of-the-funnel Sourcing & Screening platform is specially formulated for smart Recruiters like you, thus transforming the way sourcing and screening are done today.

Our Hyper-automation platform allows you to screen candidates, complete role-fit assessments, manage interviews, and provide real-time recruitment insights (analytics). LitmusBlox offers extremely powerful yet easy to use tools to attract, engage, and hire candidates at scale.

As a matter of fact, LitmusBlox can help you reduce the number of interviews by 50% and overall effort by up to 70% to hire the top talent.

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