Flaresight

NLP Developer

Flaresight

NLP Developer

NLP Developer

Flaresight

Kathmandu
Key Skills: Software Development Python (Programming Language) Artificial Intelligence (Ai) Natural Language Processing (Nlp) Large Language Models (Llm)

NLP Developer

Views: 31 | Apply Before: 2 weeks, 4 days from now

Basic Job Information

Job Category : IT & Telecommunication
Job Level : Entry Level
No. of Vacancy/s : [ 1 ]
Employment Type : Full Time
Job Location : Kathmandu
Apply Before(Deadline) : Jul. 18, 2024 23:30 (2 weeks, 4 days from now)

Job Specification

Education Level : Under Graduate (Bachelor)
Experience Required : Not Required
Professional Skill Required : Software Development Python (Programming Language) Artificial Intelligence (Ai) Natural Language Processing (Nlp) Large Language Models (Llm)

About the job

We are seeking a highly skilled and motivated NLP Developer with expertise in Large Language Models (LLM) to join our dynamic team. The ideal candidate will be responsible for designing, developing, and implementing state-of-the-art NLP solutions to address complex business problems. This role requires a deep understanding of natural language processing techniques, machine learning algorithms, and the ability to work with large-scale language models.

Key Responsibilities:

  • Develop and Implement NLP Solutions: Design and implement NLP models and algorithms for various applications such as text classification, sentiment analysis, named entity recognition, machine translation, and more.
  • Leverage LLMs: Utilize large language models (e.g., GPT, BERT, T5) to develop advanced NLP solutions and enhance existing systems.
  • Data Preprocessing and Analysis: Perform data preprocessing, cleaning, and transformation to prepare datasets for training and evaluation of NLP models.
  • Model Training and Optimization: Train and fine-tune NLP models, optimize them for performance, and deploy them into production environments.
  • Collaborate with Cross-functional Teams: Work closely with data scientists, software engineers, and product managers to understand requirements and deliver high-quality NLP solutions.
  • Research and Innovation: Stay up-to-date with the latest advancements in NLP and LLM technologies, and drive innovation by integrating new techniques and methodologies into the development process.
  • Performance Monitoring and Improvement: Monitor the performance of deployed models, identify areas for improvement, and implement necessary enhancements to ensure optimal performance.
  • Documentation and Reporting: Maintain comprehensive documentation of NLP models, algorithms, and processes, and present findings and recommendations to stakeholders.
Required Skills and Qualifications:
  • Educational Background: Bachelor's or Master’s degree in Computer Science, Data Science, Computational Linguistics, or a related field. 
  • Experience: Proven experience in developing and deploying NLP solutions, with a strong emphasis on working with large language models.
  • Technical Skills:
  • Proficiency in programming languages such as Python, and familiarity with NLP libraries/frameworks like NLTK, spaCy, Hugging Face Transformers, etc.
  • Experience with machine learning frameworks such as TensorFlow, PyTorch, or similar.
  • Strong understanding of NLP concepts, including tokenization, part-of-speech tagging, parsing, word embeddings, and transformers.
  • Analytical Skills: Excellent analytical and problem-solving skills, with the ability to work with large datasets and extract meaningful insights.
  • Communication: Strong verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
  • Team Player: Ability to work effectively in a team-oriented environment and collaborate with cross-functional teams.
  • Adaptability: Willingness to learn and adapt to new technologies and methodologies in a rapidly evolving field.

Preferred Qualifications:

  • Advanced Knowledge: Experience with specific large language models such as GPT-3, BERT, or similar.
  • Project Experience: Previous experience in working on large-scale NLP projects in industry or academia.
  • Cloud Platforms: Familiarity with cloud platforms such as AWS, Google Cloud, or Azure for deploying NLP models.
  • Open Source Contributions: Contributions to open-source NLP projects or publications in reputable NLP conferences/journals.

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