Possessing a postgraduate degree in a quantitative field like Computer Science, Data Science, Statistics, or Mathematics,
Over 6 years of professional experience. This includes both individual contributions to AI solution development and team management for the creation of high-quality data products.
Demonstrating a keen passion for data and AI, with a track record of leveraging this enthusiasm to educate others.
Possessing a robust understanding of AI engineering best practices, object-oriented concepts, and the intricacies of data-focused development.
Expertise lies in Python (including its data wrangling and machine learning libraries) and C/C++. Demonstrating a solid grasp and practical application of natural language processing, large language models, and machine learning to address tangible business challenges.
Familiarity extends to various Large Language Model (LLM) architectures, including models such as GPT, Llama, Mixtral, and Claude.
Proven experience involves customizing LLMs for specific applications through fine-tuning techniques like PEFT, RAG, and prompt engineering.
Additionally, well-versed in evaluating and benchmarking LLMs using frameworks like Arthur Bench. Boasting extensive familiarity with the entire AI software development cycle from design to deployment, utilizing frameworks such as LangChain.
Proficient in basic DevOps techniques, including CI/CD and infrastructure-as-code.
ο»ΏA track record of working in at least one cloud environment, with particular emphasis on AWS being a significant advantage.