The common responsibilities for this position include conducting research on AI and machine-learning techniques, developing and implementing algorithms for AI projects including large language models (LLM) and deep learning, collaborating with business owners to integrate domain-specific knowledge into AI projects, proposing, modifying, evaluating, and optimizing machine learning and deep learning models, conducting preprocessing for training models, training AI models using techniques such as prompt engineering and fine-tuning, developing computer vision applications, implementing Retrieval-Augmented Generation (RAG) pipelines, and integrating AI applications with automation tools. Additionally, the role involves designing and building data pipelines, maintaining AI models for various applications, ensuring the scalability and reliability of deployed AI solutions, and monitoring and optimizing model performance in production environments.
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.
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.
Job classifications that have advertised a position
Academic degree required as indicated by all job postings
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