ML Engineer

Location: Charlotte, NC or Malvern, PA (hybrid – 3 days/week from office) Duration: 06 months yrs of exp: 10 Job Description: Overview: 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 to evolving requirements. Build and maintain data pipelines: Design and implement ETL processes to support 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 to deliver robust ML solutions. Drive architecture and engineering best practices: Lead efforts to establish 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: o SageMaker o Lambda o Glue o S3 o IAM o CodeCommit o CodePipeline o 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: To build 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.