Key Responsibilities:
- Design, implement, and fine-tune large language models (LLMs) for various applications, including natural language understanding, generation, and conversation systems.
- Collaborate with data scientists and product teams to gather requirements and define project scope for LLM initiatives.
- Conduct experiments to improve model performance, including hyperparameter tuning and architecture modifications.
- Develop and maintain robust machine learning pipelines for data processing, model training, and deployment.
- Evaluate and implement the latest advancements in LLM research to keep our technology competitive.
- Monitor model performance post-deployment, ensuring reliability and accuracy in real-world applications.
- Document methodologies, results, and best practices for model development and implementation.
- Participate in code reviews and contribute to the team’s knowledge-sharing efforts.
Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, or a related field.
- Proven experience in developing and deploying large language models using frameworks such as TensorFlow, PyTorch, or similar.
- Strong understanding of NLP techniques and best practices.
- Familiarity with transformer architectures (e.g., BERT, GPT) and experience with pre-trained models.
- Proficient in programming languages such as Python, with experience in libraries such as Hugging Face Transformers, NLTK, or spaCy.
- Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and containerization technologies (e.g., Docker, Kubernetes).
- Excellent problem-solving skills and ability to work collaboratively in a team environment.
- Strong communication skills, with the ability to explain complex concepts to non-technical stakeholders.