Model Development:
● Design, develop, and enhance NLP and LLM models for diverse applications including customer support, chatbots, and automated assistance tools.
● Conduct research and experiments to advance the state-of-the-art in NLP and LLM.
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.
Education:
● Master’s or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
Experience:
● 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).
Skills:
● 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.
Preferred Qualifications:
● Experience with multilingual NLP and cross-lingual transfer learning.
● Familiarity with MLOps practices and tools for continuous integration and deployment of ML models.
● Knowledge of distributed computing and big data processing frameworks (e.g., Apache Spark).