| Full Stack ML Engineers at Malvern, Pennsylvania, USA |
| Email: [email protected] |
| From: Farha khan, Tek Inspirations LLC [email protected] Reply to: [email protected] Job Description - Job Title: Full Stack ML Engineers Location: Malvern, PA Contract: 6 Months Must be Local candidates and LinkedIn is required* Need Strong Candidates on This role* JD: Full Stack ML Engineers 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." Keywords: artificial intelligence machine learning sthree Pennsylvania Full Stack ML Engineers [email protected] |
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| Wed Jul 10 07:39:00 UTC 2024 |