What are the responsibilities and job description for the AI/ML Architect (Snowflake, ETL, AWS Databricks, AI/ML) position at Noblesoft Technologies?
Role - AI/ML Architect ( Snowflake, ETL, AWS Databricks, AI/ML )
Location - Torrance, CA (DAY 1 Onsite )
In person Interview
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.
Thanks and Regards,
Akash
Location - Torrance, CA (DAY 1 Onsite )
In person Interview
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.
Thanks and Regards,
Akash