ML Engineer

ML Engineer

Location: Charlotte, NC or Malvern, PA (hybrid3 days/week from office)

Duration: 06 months

yrs of exp:10

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.

Qualification

Bachelor's Degree