Data Management:
- Collect, preprocess, and curate large datasets for training and evaluation of NLP, LLM models.
- Implement data augmentation and enhancement techniques to improve model robustness.
Model Deployment:
- Deploy and maintain NLP, LLM models in production environments, ensuring high availability and performance.
- Develop APIs and services to make NLP, LLM capabilities accessible to other teams and applications.
Collaboration:
- Work closely with data scientists, software engineers, and domain experts to understand requirements and deliver tailored NLP solutions.
- Provide technical guidance and mentorship to junior team members.
Performance Monitoring:
Implement monitoring and logging for deployed models to ensure performance, reliability, and scalability.
Conduct regular evaluations and fine-tuning of models based on feedback and new data.
Documentation and Reporting:
- Document methodologies, experiments, and results comprehensively.
- Communicate findings and progress to stakeholders through reports and presentations.
Continuous Improvement:
- Stay updated with the latest advancements in NLP, LLM, and AI research.
- Contribute to the continuous improvement of the team's processes, tools, and methodologies.
Job requirement
- Master’s or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- Minimum of 3-5 years of experience in developing and deploying NLP, LLM models.
- Proven experience with large language models (e.g., GPT, BERT, llama, Mistral ..) and deep learning frameworks (e.g., TensorFlow, PyTorch).
- Strong programming skills in Python and familiarity with NLP libraries (e.g., Hugging Face Transformers, spaCy, NLTK).
- Expertise in machine learning algorithms, neural networks, and statistical modeling.
- Experience with cloud platforms (e.g., AWS, GCP, Azure)
- Strong problem-solving skills and the ability to work independently and collaboratively.