Title: Machine Learning Architect
Location: Basking Ridge, NJ OR Rochelle Park, NJ (Hybrid)
Duration: 6-12+ Months
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Hybrid: 3 to 5 days a week in the office (Basking Ridge, NJ or Rochelle Park, NJ)
Experience
7+ years experience in designing and developing enterprise class AI Platforms and solutions
3+ years of experience with enterprise fully automated Model and Risk management solution.
3+ years implementing Data ops, Client ops
MS or BS in Computer Science, Information Science, Engineering or other related field
Skills: Deep understanding and hands on experience with Client Engineering techniques and tools including hands on experience with Client Operations.
Experience with the primary managed data services within Google Cloud Platform , including AI Vertex, Cloud Bigtable, Cloud Spanner, Cloud SQL, or BigQuery
Proficient in Data Science workbenches such as Domino, Container platform such as K8s/Docker, Core Java, J2EE, JSP, Servlet, Node.js, Angular,
Proficient in Big Data Technologies , Data Transport (Pulsar/Kafka), Spark, Jupyter/ Python.
Experience working with multiple databases: Cassandra, PostGreS, Teradata. and NoSQL and RDBMS Technologies Container platform such as K8s/Docker,
Experience with various agile methodologies and tools: JIRA, Confluence, Gitlab, CICD, etc.
Exposure to product based development methodology is desirable
Strong leadership, communication, persuasion and teamwork skills
Client Model Management Platform Strategy:
Define and Architect comprehensive Model Management framework across these 4 major areas
o Monitor Data Quality - Monitor drift in data quality.
o Monitor Model Quality - Monitor drift in model quality metrics, such as accuracy.
o Monitor Bias Drift for Models in Production - Monitor bias in model's predictions.
o Monitor Feature Attribution Drift for Models in Production - Monitor drift in feature attribution.
Technology / Execution
Build and implement a platform for Seamless integration and interface with existing Batch and Realtime Client systems to enable track performance metrics and verify the accuracy of predictions
Design/Implement a clean UI so that Data drift, model quality, and other health statistics are provided in an easy-to-understand interface to enable quick assessment of the business impact and initiate proactive actions
Implement appropriate notifications, alerts for both upstream and downstream systems. --