Senior AWS Machine Learning Engineer

2 days ago

Apply Now

Receive Emails with Similar Jobs

Spinify

WebsiteLinkedInAll Job Openings

Level up motivation, results, and engagement with Spinify. Ready to take your team's game to the next level?

Gamification • Incentive Competitions • Employee Engagement • Employee Motivation • Productivity

11 - 50

💰 Pre Seed Round on 2016-04

Description

• Designing, developing, and deploying AI-powered solutions for personalized learning and coaching feedback. • Building and deploying scalable Machine Learning models using AWS SageMaker. • Developing and managing real-time data pipelines using AWS Kinesis and AWS Glue. • Designing and optimizing natural language querying using AWS Q for performance data insights. • Utilizing Amazon Personalize for dynamic learning paths and recommendations. • Implementing emotional intelligence analysis with Amazon Rekognition and Comprehend. • Building real-time dashboards using Amazon QuickSight for performance visualization. • Creating serverless workflows with AWS Lambda and API Gateway for coaching suggestions. • Integrating generative AI models using AWS Bedrock.

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.