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Job title: Data Architect With AI/ML (Local to California)
Location - Torrance, CA (Onsite)
Job type: Full time and Contract c2c both
Interview: Video
JD -
Enterprise Data and AI Architect to drive the Data and AI initiatives from ideation, design and deployment.
Key Responsibilities:
AI/ML Strategy: Design the architectural framework for scaling Artificial Intelligence and Machine Learning models. This includes building pipelines for LLMs, Generative AI, and predictive analytics. AWS Cloud Governance: Act as the lead architect for AWS environments, ensuring best practices in VPC design, serverless architectures (Lambda), and cost optimization (FinOps). Data Mesh & Analytics: Overhaul legacy data silos into a modern Data Lakehouse or Data Mesh architecture to support real-time business intelligence and data-driven decision-making. AI Ethics & Security: Establish guardrails for data privacy in AI models and ensure AWS security protocols (IAM, GuardDuty) are strictly followed.
Required Skills: Cloud Platform: Proficiency in AWS Ecosystem (S3, SageMaker, Redshift, Glue, Bedrock, and EKS). Data Frameworks: Experience with Snowflake, Databricks, or Apache Spark for large-scale data processing. AI Frameworks: Familiarity with PyTorch, TensorFlow, or LangChain for integrating AI into enterprise workflows. Automation: Strong background in IaC (Infrastructure as Code) using Terraform or AWS CloudFormation.
Preferred Qualifications: AWS Certifications: Highly preferred (e.g., AWS Certified Solutions Architect Professional or AWS Certified Data Engineer). Analytics Background: Proven track record of designing platforms that handle Petabyte-scale data and complex ETL/ELT processes. AI Integration: Experience moving AI projects from "Proof of Concept" (PoC) to full-scale enterprise production.
Job title: Data Architect With AI/ML (Local to California)
Location - Torrance, CA (Onsite)
Job type: Full time and Contract c2c both
Interview: Video
JD -
Enterprise Data and AI Architect to drive the Data and AI initiatives from ideation, design and deployment.
Key Responsibilities:
AI/ML Strategy: Design the architectural framework for scaling Artificial Intelligence and Machine Learning models. This includes building pipelines for LLMs, Generative AI, and predictive analytics. AWS Cloud Governance: Act as the lead architect for AWS environments, ensuring best practices in VPC design, serverless architectures (Lambda), and cost optimization (FinOps). Data Mesh & Analytics: Overhaul legacy data silos into a modern Data Lakehouse or Data Mesh architecture to support real-time business intelligence and data-driven decision-making. AI Ethics & Security: Establish guardrails for data privacy in AI models and ensure AWS security protocols (IAM, GuardDuty) are strictly followed.
Required Skills: Cloud Platform: Proficiency in AWS Ecosystem (S3, SageMaker, Redshift, Glue, Bedrock, and EKS). Data Frameworks: Experience with Snowflake, Databricks, or Apache Spark for large-scale data processing. AI Frameworks: Familiarity with PyTorch, TensorFlow, or LangChain for integrating AI into enterprise workflows. Automation: Strong background in IaC (Infrastructure as Code) using Terraform or AWS CloudFormation.
Preferred Qualifications: AWS Certifications: Highly preferred (e.g., AWS Certified Solutions Architect Professional or AWS Certified Data Engineer). Analytics Background: Proven track record of designing platforms that handle Petabyte-scale data and complex ETL/ELT processes. AI Integration: Experience moving AI projects from "Proof of Concept" (PoC) to full-scale enterprise production.