Description:

• ML frameworks, libraries, data structures, data modelling, and software architecture.

• Knowledge of mathematics, statistics, and algorithms.

• ML models development and evaluation process.

• ETL/ELT practices such profiling, cleansing, transforming, developing and documenting data structures, schemas and dictionaries.

• High proficiency in software development best practices.

• MLOps/DevOps and CI/CD in a data science/machine learning settings, (e.g. Shell Scripting, Jenkins, Code Build, Testing)

• High proficiency in automating, pipelines using AWS Platform Services includin S3, Lambda, CloudWatch, Step Function, ECS, Dockers, Sagemaker.

• Nice to have exposure to machine learning for NLP

• Comfortable in a high-paced project

• Strong work ethic, delivery focused

Skills:

• python
• aws lambda
• etl
• machine learning
• terraform
• jenkins

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