NLP Engineer

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. #J-18808-Ljbffr Kula Example