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    Principal Architect - Mumbai, India - Quantiphi

    Quantiphi
    Default job background
    Technology / Internet
    Description

    Role: Principal Architect -AI/ML

    Experience in Years : 14-20

    Work location: Mumbai/ Bangalore (Hybrid)

    Responsibilities:

    • More than 15 years of experience in analytics, solutioning, and technical roles.
    • 5+ years of experience in building, delivery ML/AI workloads on Cloud (GCP/AWS/Azure) (For an Engineering Leader it should be at least 8+ years in AI-ML)
    • Experience in architecting, designing, and implementing end to end ML implementation, POC to production
    • Experience of having worked in distributed computing and enterprise environments like Hadoop, GCP/AWS/Azure Cloud.
    • Well versed with various Data Integration, and ETL technologies on Cloud like Spark, Pyspark/Scala, Dataflow, DataProc, EMR, etc. on various Cloud.
    • Experience of having worked with traditional ETL tools like Informatica/DataStage/OWB/Talend, etc.
    • Deep knowledge of one or more Cloud and On-Premise Databases like Cloud SQL, Cloud Spanner, Big Table, RDS, Aurora, DynamoDB, Oracle, Teradata, MySQL, DB2, SQL Server, etc.
    • Exposure to any of the No-SQL databases like Mongo dB, CouchDB, Cassandra, Graph dB, etc.
    • Experience in architecting and designing scalable data warehouse solutions on cloud on Big Query or Redshift
    • Provide technical expertise and guidance in AI/ML technologies and methodologies to the Technical Architects and ML engineers.
    • Need to stay up to date with the latest advancements in the field of AI-ML ,Data Science and Data Analytics and also guide the team in applying best practices and innovative solutions.
    • Drive research activities to explore new AI/ML technologies, techniques and processes.
    • Should be able to collaborate with cross-functional teams, sales and pre-sales team, and business stakeholders, to understand requirements, align priorities, and drive the integration of AI/ML solutions into services
    • Ensure the quality and performance of AI/ML models, systems, and algorithms.
    • Establish rigorous testing and validation processes to deliver reliable and scalable solutions.
    • Should be able to monitor and optimize performance metrics to drive continuous improvement
    • Contribute to the development of AI/ML strategy and roadmaps aligned with business goals.
    • Foster a culture of continuous learning and development within the team

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