Full-Time Sr. ML Engineer

• Pipeline Refactoring & Optimization
• Redesign and refactor existing ML pipelines to improve scalability, maintainability, and operational efficiency.
• Migrate pipelines to accommodate new input datasets that will drive updated models.
• Ensure pipelines can handle both batch and streaming workloads.
• Feature Store Integration
• Work with Tecton to manage and serve online/offline features for ML models.
• Migrate legacy feature ingestion and retrieval processes to Tecton.
• AWS Cloud Engineering & Automation
• Develop and manage infrastructure using AWS CloudFormation and other IaC tools.
• Leverage AWS services such as SageMaker, Lambda, ECR, S3, and DynamoDB for ML workflows.
• MLOps & CI/CD
• Implement and maintain deployment pipelines using AWS CodePipeline.
• Ensure seamless integration of ML workflows with SageMaker for training, inference, and monitoring.
• Apply robust testing strategies, code coverage, and quality controls to all ML pipeline code.
• Data Engineering Support
• Integrate ML pipelines with Snowflake, S3, and DynamoDB data sources.
• Optimize data ingestion, transformation, and delivery to production models.
• Technical Debt & Migration Projects
• Identify and remediate technical debt in ML infrastructure.
• Support migration of existing code to align with new feature store and data input requirements.

What is the last date for applying to the job?

Which countries are accepted for this remote job?