AI Engineer

Responsibility

The common responsibilities for this position include developing and optimizing AI models and algorithms, particularly focusing on large language models (LLMs) and deep learning techniques. This involves conducting data preprocessing, feature engineering, and model evaluation to ensure high-quality input for machine learning models. The role requires designing and implementing retrieval-augmented generation (RAG) systems, integrating AI solutions into existing platforms, and ensuring the scalability, reliability, and performance of deployed models. Collaboration with cross-functional teams is essential for integrating AI capabilities, while research on emerging AI technologies and continuous optimization of model performance are also key duties. Additionally, responsibilities encompass managing the entire model lifecycle, conducting comprehensive model testing, and providing technical expertise and support to users on AI-powered tools and applications.

Job Growth

Skills Requirement

The percentages next to each skill reflect the sector’s demands in these respective skills. E.g., 30% means this skill has been listed in 30% of all the job postings in this sector.

• Skill Categories
• Specific Skill Sets

Skills Distribution

The skills distribution tells you what specific skill sets are in demand. E.g., Skills with a distribution of “More than 50%” means that these skills are wanted in more than 50% of the job postings.

• More Than 70%
• More Than 50%
• More Than 30%
• More Than 10%