ML Engineer
ML Engineer
iSoftTek Solutions Inc
Charlotte, NC
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See who iSoftTek Solutions Inc has hired for this role
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:
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
- 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: 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
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Seniority level
Mid-Senior level -
Employment type
Full-time -
Job function
Engineering and Information Technology -
Industries
Non-profit Organizations and Primary and Secondary Education
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