Description

You will build and deploy end-to-end systems using cloud ML environments and in-house infrastructure.

Responsibilities

• Build and deploy end-to-end systems using cloud ML environments like SageMaker or in-house infrastructure.
• Develop and consume APIs and micro-services to facilitate business logic and data workflows.
• Set up and optimize SQL/NoSQL databases for production ML system usage.
• Deploy production applications to AWS cloud using serverless architecture and containers.
• Automate data pipelines to support data science and machine learning requirements.

Required Skills

• 5+ years of professional software development experience.
• Proficiency in Python and JavaScript.
• Experience deploying production applications to AWS.
• Hands-on experience with Docker and containerized environments.
• Experience with serverless architecture and cloud-native workflows.
• Working knowledge of SQL and NoSQL databases.
• Experience building and consuming APIs and micro-services.
• Degree in any field of study.

Preferred Skills

• Experience with AWS infrastructure including EC2, S3, Lambda, and Batch.
• Proficiency with Postgres, DynamoDB, and ElasticSearch.
• Experience with Vue.js, NodeJS Express, and Git/GitHub workflows.
• Understanding of Data Science and Machine Learning concepts.

Key Skills

Education

Any Graduate