| Company |
Proof of Search |
| Job title |
LLM AI Engineer |
| Job location |
Australia |
| Type |
Full Time |
Responsibilities:
- Model Development and Optimization:
- Develop and fine-tune large language models (LLMs) to improve AI-driven features.
- Optimize models for efficiency and scalability for large datasets and high transaction volumes.
- Implement state-of-the-art NLP techniques for enhanced accuracy and reliability.
- AI Integration:
- Collaborate with software engineers to integrate LLMs into existing infrastructure and products.
- Design APIs and tools for seamless incorporation of AI functionalities into applications and services.
- Data Management:
- Work with data scientists to preprocess and manage large datasets for model training and evaluation.
- Implement data augmentation and cleaning techniques to ensure high-quality inputs for model training.
- Research and Innovation:
- Stay updated with advancements in AI, NLP, and blockchain technologies.
- Conduct research to explore new methodologies and frameworks beneficial to the company’s AI initiatives.
- Publish findings and contribute to the open-source community where applicable.
- Performance Monitoring and Maintenance:
- Set up monitoring systems to track real-time performance of deployed models.
- Troubleshoot issues and implement updates or improvements for optimal performance.
- Security and Compliance:
- Ensure AI solutions adhere to industry standards and regulatory requirements.
- Implement robust security measures to protect sensitive data and maintain user privacy.
Requirements & Skills:
- Education:
- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- Experience:
- Proven experience with large language models (LLMs) and natural language processing (NLP) techniques.
- Experience in the cryptocurrency or fintech industry is a strong plus.
- Technical Skills:
- Proficiency in Python, TensorFlow, PyTorch, and other AI frameworks.
- Strong understanding of machine learning algorithms, deep learning architectures, and model optimization techniques.
- Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker, Kubernetes).
- Soft Skills:
- Excellent problem-solving skills and ability to work in a fast-paced, collaborative environment.
- Strong communication skills to articulate complex technical concepts to non-technical stakeholders.
- Proactive and innovative mindset with a passion for learning and applying new technologies.
