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Natural Language Processing Engineer
Function
Research & Development
About the Role
The Natural Language Processing Engineer develops AI systems that understand and interpret human language, enhancing communication capabilities. Their role is vital in creating more intuitive and interactive AI applications, improving user experiences, and opening new avenues for AI applications in various sectors.
Responsibilities
- Design, develop, and deploy NLP systems and algorithms that can effectively process large volumes of text data.
Collaborate with data scientists and machine learning engineers to integrate NLP technologies into broader AI systems.
Conduct research on the latest NLP methodologies and advancements to continuously improve language processing capabilities.
Work with cross
functional teams to understand business requirements and translate them into technical specifications for NLP solutions.
Implement machine learning models for tasks such as text classification, sentiment analysis, language translation, and entity recognition.
Optimize NLP systems for scalability, efficiency, and reliability.
Maintain a thorough understanding of data privacy and security measures related to processing sensitive language data.
Evaluate model performance and iterate on model design to enhance accuracy and functionality.
Document NLP system architecture, development processes, and user guides for technical and non
technical stakeholders.
Stay abreast of industry trends and emerging tools in NLP to ensure the organization remains at the forefront of technological advancements.
Required Skills
- Bachelor’s or Master’s degree in Computer Science, Linguistics, Artificial Intelligence, or a related field.
Strong programming skills in languages such as Python, Java, or C++.
Experience with NLP libraries and frameworks (e.g., NLTK, spaCy, Transformers).
Knowledge of machine learning, deep learning, and statistical analysis.
Familiarity with neural network architectures relevant to NLP (e.g., RNNs, CNNs, Transformers).
Excellent problem
solving and analytical skills.
Ability to work collaboratively in a team environment.
Strong communication skills to effectively convey complex technical concepts.
General skills in software development best practices, version control (e.g., Git), and DevOps tools.
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