About the Role
Collaborate with cross-functional teams to identify opportunities for integrating machine learning, particularly LLMs, into blockchain-related projects.
Design, develop, and implement machine learning models and algorithms, with a specific focus on LLMs, for enhancing data analysis, natural language understanding, pattern recognition, and anomaly detection in blockchain data.
Perform data preprocessing, feature engineering, and model selection to optimize model performance, with a focus on LLM-driven solutions.
Implement and maintain machine learning pipelines and workflows, ensuring scalability and efficiency, while leveraging LLM capabilities.
Stay up-to-date with the latest advancements in machine learning, LLMs, and blockchain technologies, and actively contribute to research and development efforts in these areas.
Debug and troubleshoot machine learning models and systems, especially those utilizing LLMs, as well as optimize their performance.
Requirements
Bachelor's or Master's degree in Computer Science, Data Science, or a related field (or equivalent work experience).
Proven experience in machine learning, deep learning, and data analysis, with a strong portfolio showcasing your work, including LLM-related projects.
Expertise in programming languages such as Python and proficiency in relevant libraries, including TensorFlow, PyTorch, scikit-learn, and LLM frameworks like GPT-3 or BERT.
Strong understanding of blockchain technology and its principles is a significant advantage.
Knowledge of data manipulation, preprocessing, and feature engineering techniques.
Experience with cloud platforms, big data technologies, and distributed computing is a plus.
Strong problem-solving skills and the ability to work collaboratively in a fast-paced environment.
Excellent communication and presentation skills.