Lead a team responsible for developing end-to-end (Data/Dev/ML)Ops pipelines based on in-depth understanding of cloud platforms, AI lifecycle, and business problems to ensure analytics solutions are delivered efficiently, predictably, and sustainably.
Build strong foundations in Data Engineering: communication skills to interact with Data Subject Matter Experts, metadata management, data cleaning, data pipeline design, implementation and maintenance.
Should Be Experienced with: Apache Spark, AWS Glue Data Catalog, AWS Glue ETL Jobs
Solid understanding of the Machine Learning Model Development Lifecycle: Exploratory Data Analysis, Feature Engineering, ML Evaluation & Tuning, Model Monitoring
Strong Data Visualization skills
Expertise working with the following Python packages: Numpy, Pandas, Matplotlib
Continuously evaluate the latest packages and frameworks in the ML ecosystem
Strong technical documentation writing skills
Experience working with Deep Learning Frameworks: Pytorch, Tensorflow/Keras