Job Description: AI/ML Engineers
As an AI/ML Engineer, your core responsibilities include:
Programming and Pipeline Development
- Proficiency in Python with at least 5 years of experience.
- Building pipelines in Python/PySpark using libraries such as NumPy, pandas, scikit-learn.
Data Science & Modeling
- Developing data science models including XGBoost, Regression, etc.
- Performing Data Preprocessing: Cleaning, transforming, and augmenting datasets to make them ML-ready.
- Performing Feature Engineering to identify and create relevant features to improve model accuracy and interpretability.
- Conducting Exploratory Data Analysis (EDA) with visualization tools like matplotlib, seaborn.
Version Control & Optimization
- Proficiency with Git and version control systems.
- Writing clean, optimized code suitable for production, utilizing techniques such as vectorization and concurrency.
Containerization & CI/CD
- Familiarity with Docker or similar containerization tools for reproducible environments.
- Experience with CI/CD pipelines, especially with Git-based CI/CD methods to integrate ML models into deployment workflows.
Cloud & Infrastructure
- Knowledge of various AWS services including Lambda, API Gateway, Glue, Athena, S3, Iceberg.
- Familiarity with Azure AI Studio for model hosting, GPU/TPU usage, and creating scalable infrastructure.
- Experience with AWS GIS (Glue Interactive) and AWS Sagemaker.
Additional Skills
- Good communication skills.
- Domain knowledge of Retail Investment is a plus.
Note: This role requires experience with model deployment and management within cloud environments.