AI/ML Architect

Role

• Data Architect with AWS and AI/ML Location
• Torrance, CA 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.