Senior AWS Machine Learning Engineer

2 days ago

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Description

• Responsible for designing, developing, and deploying AI-powered solutions. • Build and deploy scalable Machine Learning models using AWS SageMaker. • Develop and manage real-time data pipelines using AWS Kinesis and AWS Glue. • Design and optimize natural language querying using AWS Q. • Use Amazon Personalize for dynamic, personalized learning paths. • Implement emotional intelligence analysis with Amazon Rekognition and Amazon Comprehend. • Build real-time dashboards using Amazon QuickSight. • Create serverless workflows using AWS Lambda and API Gateway. • Work with AWS Bedrock to integrate generative AI models. • Ensure data privacy and security across all services using AWS IAM.

Requirements

• 5+ years of experience with AWS Cloud Services, particularly SageMaker, Kinesis, Glue, Lambda, Personalize, and QuickSight. • Strong background in machine learning, including model training, optimization, and deployment using AWS SageMaker. • Experience in building and managing real-time data pipelines using Kinesis and integrating large datasets using Glue or other ETL tools. • Expertise in Natural Language Processing (NLP), with practical experience using Amazon Comprehend and Amazon Transcribe for sentiment and text analysis. • Familiarity with AWS Bedrock and integrating generative AI models into real-world applications. • Strong programming skills in Python and SQL. • Experience with API development using API Gateway and Lambda for creating serverless, scalable APIs. • Experience building real-time data visualizations and dashboards using Amazon QuickSight. • Knowledge of data security best practices, including working with AWS IAM and compliance frameworks such as GDPR and SOC2. • Strong analytical and problem-solving skills, with the ability to optimize performance and scale solutions.

Benefits

• Competitive salary with performance-based bonuses. • Remote work flexibility. • Opportunity to work with cutting-edge AI and cloud technologies. • A collaborative and innovative team environment. • Opportunities for professional development and growth in the AI and ML space.