NLP Engineer
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Why you should join us:
- You want to be one of the *first* engineers in a growing startup.
- You want to join strong technical founders that have bootstrapped a company into profitability.
- You want to grow as an engineer by using all levels of the stack rather than one thing.
- You want to make an impact on the product because you are the target audience of our product.
- You want to make an impact on the technical decisions because you're an expert in your field.
What you'll do:
- Develop highly scalable classifiers and tools leveraging machine learning, data regression, and rules-based models
- Proactive in seeking opportunities for innovation
- Highly communicative with collaborators and manager
- Work independently, able to manage multiple projects simultaneously
- Ability to build APIs and libraries for Python.
Skills and knowledge you should possess:
- Ph.D./M.Sc degree in Computer Science, Artificial Intelligence, Machine Learning, or related technical field, or equivalent practical experience.
- Proven experience as an ML Engineer or similar role
- NLP experience is a must
- CV experience is a plus
Anima focuses on Mobile, Developer Tools, Designers, and User Interface Design. Their company has offices in New York City and Tel Aviv-Yafo. They have a small team that's between 11-50 employees.
You can view their website at http://www.animaapp.com or find them on Twitter, Facebook, and LinkedIn.
What does NLP Engineer do?
A Natural Language Processing (NLP) Engineer is a professional who designs and develops software systems that can understand and generate human language
They typically work with machine learning and artificial intelligence (AI) technologies to create NLP solutions for various applications, including chatbots, virtual assistants, search engines, sentiment analysis, and language translation
NLP engineers play a critical role in developing software systems that can understand and generate human language, enabling us to interact with technology in more natural and intuitive ways
The role of an NLP Engineer includes:
- Data preprocessing: NLP engineers are responsible for cleaning, normalizing, and transforming raw text data into a format that can be used by machine learning algorithms.
- Feature engineering: NLP engineers design and develop features that are relevant to the NLP problem they are trying to solve. They extract features such as word frequency, part-of-speech tagging, and sentiment analysis.
- Building machine learning models: NLP engineers use machine learning algorithms such as deep learning, neural networks, and decision trees to train models that can understand and generate human language.
- Evaluating and improving models: NLP engineers evaluate the performance of their models using various metrics such as accuracy, recall, and F1 score. They also use techniques such as cross-validation and hyperparameter tuning to improve model performance.
- Integration: NLP engineers integrate their NLP solutions into larger software systems or platforms, such as chatbots or virtual assistants.