AI/NLP Engineer

Responsibilities:

• Design, develop, and deploy NLP algorithms and models to extract structured information from unstructured text data.
• Build and optimize text classification, entity recognition, sentiment analysis, and language generation systems.
• Collaborate with data scientists to preprocess and prepare textual data for analysis and modeling.
• Explore and evaluate new NLP techniques, tools, and libraries to improve model performance and scalability.
• Work closely with software engineers to integrate NLP models into production systems and applications.
• Conduct experiments and perform rigorous testing to validate the accuracy and robustness of NLP models.
• Stay up-to-date with the latest advancements in NLP research and technologies, and actively contribute to the company's knowledge base.
• Provide technical guidance and mentorship to junior team members, fostering a culture of learning and innovation.

Requirements:

1. Bachelors degree in computer science, Engineering, or related field; Master's or Ph.D. preferred.
2. Proven experience ) in developing NLP solutions, including text classification, entity recognition, sentiment analysis, and language generation.
3. Strong proficiency in programming languages such as Python, Java, or C++, and familiarity with NLP libraries such as NLTK, SpaCy, or TensorFlow.
4. Solid understanding of machine learning techniques and algorithms, with practical experience in building and deploying ML models.
5. Experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras, and proficiency in training neural network models for NLP tasks.
6. Knowledge of linguistics and familiarity with linguistic concepts such as syntax, semantics, and pragmatics.
7. Excellent problem-solving skills and the ability to work independently as well as part of a collaborative team.
8. Strong communication skills and the ability to effectively convey technical concepts to both technical and non-technical stakeholders.
9. Experience with big data technologies such as Apache Hadoop, Spark, or Elasticsearch is a plus.
10. Demonstrated track record of publications, patents, or contributions to open-source NLP projects is highly desirable.