LLM Engineer (Large Language Model)
SKILLS
FULL DESCRIPTION
Summary
The LLM Engineer will develop and fine-tune large language models, optimizing them for performance and efficiency. They will collaborate with researchers, build data pipelines, and monitor model performance.
Key Responsibilities
- Develop and fine-tune large language models for specific applications.
- Optimize LLMs for performance, scalability, and deployment efficiency.
- Collaborate with researchers and data scientists to implement cutting-edge techniques.
- Build pipelines for data collection, preprocessing, and model evaluation.
- Monitor and address issues in LLM performance and reliability.
Key Qualifications
- Strong experience with Python and AI frameworks like PyTorch or TensorFlow.
- Proficiency in transformer architectures (e.g., GPT, BERT).
- Expertise in natural language processing (NLP) and large-scale data handling.
- Familiarity with distributed training and cloud-based AI environments.
- Master’s or Ph.D. in AI, Computer Science, or related field preferred.
Responsibilities:
Develop and fine-tune large language models for specific applications. Optimize LLMs for performance, scalability, and deployment efficiency. Collaborate with researchers and data scientists to implement cutting-edge techniques. Build pipelines for data collection, preprocessing, and model evaluation. Monitor and address issues in LLM performance and reliability.
Requirements:
Strong experience with Python and AI frameworks like PyTorch or TensorFlow. Proficiency in transformer architectures (e.g., GPT, BERT). Expertise in natural language processing (NLP) and large-scale data handling. Familiarity with distributed training and cloud-based AI environments. Master’s or Ph.D. in AI, Computer Science, or related field preferred.