Senior Data Scientist & AI Engineer (MLOps, Cloud)
Summary
Build and deploy AI models end-to-end in the cloud, focusing on MLOps, deep learning, and GenAI systems using Python, AWS, and frameworks like LangChain.
Qualifications
- Bachelor's or Master's degree in Computer Science, Data Science, Statistics, Mathematics, Engineering, or a related quantitative discipline.
- 3+ years of active data science
- High proficiency in problem-solving for data science (e.g., with suitable frameworks like MECE, root cause analysis, etc.).
- Familiarity in MLOps as a framework, with strong experience in end-to-end model development and deployment in the cloud (e.g., AWS).
- Seasoned in the theory and execution of deep learning algorithms and architectures (e.g., transformer models, reinforcement learning), AI Engineering (e.g., neural embeddings, LLM models, building of GenAI systems with frameworks like LangChain and LangGraph, vector databases, EDD, etc.), optimization, statistical modelling, and multi-criteria decision analysis.
- Experience with data engineering for data science (e.g., ELT concepts, structured tabletransformation experience, database technologies, etc)
- Superb communication and visualization abilities.
- Strong programming and development skills in Python (and accompanying frameworks), R, SQL, Shell scripting