Full Stack Machine Learning Engineer

Job Description:

We are seeking Full Stack ML Engineers to support the Hyper Personalization program for our Wealth client, a key initiative aimed at enhancing personalization within financial services.

This role requires strong delivery-focused individuals with a deep understanding of the AWS tech stack and financial services personalization.

Responsibilities:

Integrate AI/ML models with multiple data sources: Ensure seamless data flow in and out of models.
Fine-tune existing models: Optimize performance and adapt models tevolving requirements.
Build and maintain data pipelines: Design and implement ETL processes tsupport model integration.
Monitor and manage ML models in production: Implement MLOps practices for model monitoring, tracking, and maintenance.
Collaborate with cross-functional teams: Work closely with data scientists, data engineers, and other stakeholders tdeliver robust ML solutions.
Drive architecture and engineering best practices: Lead efforts testablish and enforce best practices in building the integration framework.

Technical Skills:

Proficiency in Python and SQL databases: Essential for data manipulation and integration tasks.
Experience with AWS cloud services: Including but not limited to:
SageMaker
Lambda
Glue
S3
IAM
CodeCommit
CodePipeline
Bedrock
Experience with data pipeline and workflow management tools: Such as Apache Airflow or AWS Step Functions.
Understanding of ETL techniques, data modeling, and data warehousing concepts: Tbuild efficient data pipelines.
Familiarity with AI/ML platforms and tools: Including TensorFlow, PyTorch, MLflow, and others.
Knowledge of MLOps practices: Including model monitoring, data drift detection, and pipeline automation.
Experience with Docker and AWS ECR: For containerization of ML applications.