NLP Engineer

Kula Example; San Francisco (CA); On-site; USD 120,000 - 170,000; Full time

Job summary

Kula Example is seeking an NLP Engineer to design and deploy natural language understanding systems powering our core product in San Francisco. The role focuses on building robust text classification, entity extraction, and conversational AI features using Python, PyTorch, and Hugging Face Transformers.

The ideal candidate has 3+ years in NLP/NLU, hands-on experience with LLMs, fine-tuning, and prompt engineering, and holds an MS in CS or a related field.

Qualifications

• 3+ years in NLP/NLU
• Strong Python
• Experience with LLMs, fine-tuning, and prompt engineering
• Strong background in NLP and deep learning
• Excellent knowledge of Python and NLP libraries
• Master’s degree in Computer Science or related field

Responsibilities

• Build and deploy text classification and entity extraction pipelines.
• Develop and optimize conversational AI models.
• Collaborate with product and data teams to ship NLP features end-to-end.
• Work with cross-functional teams to understand product requirements and develop NLP solutions.
• Design and maintain NLP-based models and pipelines using Python, PyTorch, and Hugging Face Transformers.

Education

MS in CS or related field

Tools

Python

PyTorch

Hugging Face Transformers

Job description

About the Job

About: We are seeking an NLP Engineer to design and deploy natural language understanding systems powering our core product.

Requirements: 3+ years in NLP/NLU, proficiency in Python, PyTorch, and Hugging Face Transformers. Experience with LLMs, fine-tuning, and prompt engineering. MS in CS or related field. The ideal candidate should have a strong background in NLP and deep learning, with excellent knowledge of Python and popular NLP libraries. A master’s degree in Computer Science or a related field is also required.

Responsibilities: At showcase, the NLP Engineer will be responsible for building and deploying text classification and entity extraction pipelines, developing and optimizing conversational AI models, and collaborating with the product and data teams to ship NLP features end-to-end. The role will involve working closely with cross-functional teams to understand product requirements and develop NLP solutions that meet these needs. Key responsibilities include:

Building and deploying text classification and entity extraction pipelines to enable accurate and efficient data processing.

Developing and optimizing conversational AI models to improve user experience and engagement.

Collaborating with the product team to understand product requirements and develop NLP features that meet these needs.

Working closely with the data team to develop and deploy NLP-based data pipelines that support data-driven decision-making.

Designing and implementing NLP-based solutions to address complex technical problems and improve overall system performance.

Developing and maintaining NLP-based models and pipelines using Python, PyTorch, and Hugging Face Transformers.

Staying up-to-date with the latest developments in NLP and deep learning, and applying this knowledge to improve our NLP solutions.

Skills: The ideal candidate should have excellent knowledge of NLP and deep learning, with a strong background in Python and popular NLP libraries. Key skills include:

Proficiency in Python, PyTorch, and Hugging Face Transformers.

Experience with LLMs, fine-tuning, and prompt engineering.

Strong understanding of NLP concepts, including tokenization, stemming, lemmatization, and named entity recognition.

Ability to design and implement NLP-based solutions to address complex technical problems.

Excellent communication and collaboration skills, with the ability to work closely with cross-functional teams.

Strong problem-solving skills, with the ability to analyze complex problems and develop effective solutions.

Ability to stay up-to-date with the latest developments in NLP and deep learning, and apply this knowledge to improve our NLP solutions.