Google Cloud Platform ML Architect -Data - Full Time

Overview

On Site
Full Time

Skills

GCP
ML

Job Details

Role: Google Cloud Platform ML Architect -Data
Location: Chaska, MN (100% onsite)
Hire type: FTE

Detailed JD:
Key Responsibilities:

  • Design end-to-end data solutions, including data ingestion, storage, processing, and analysis pipelines, as well as machine learning model development, deployment, and monitoring pipelines.
  • Design and implement scalable, secure, and cost-optimized cloud infrastructure using Google Cloud Platform services like Big Query, Dataflow, DataProc, Cloud Storage, and Kubernetes Engine.
  • Design and implement data models, ensuring data consistency, accuracy, and accessibility for various applications and users.
  • Establish MLOps practices, enabling the automation of machine learning model training, deployment, and monitoring.
  • Ensure that all data solutions adhere to security and compliance standards, implementing access controls, encryption, and other security measures.
  • Monitor and optimize the performance of data and machine learning systems, ensuring they meet business requirements and SLAs.
  • Develop and implement strategies for managing and optimizing cloud costs, ensuring efficient resource utilization.
  • They provide technical guidance and mentorship to other team members, fostering a culture of best practices and continuous improvement.

Key Skills:

  • 10+ years of experience designing and developing production grade data architectures using google cloud data services and solutions
  • Proficiency in Big Query, Dataflow, Data proc, Cloud Storage, pub-sub, Kubernetes Engine, and other relevant Google Cloud Platform services.
  • Strong Experience with data warehousing, ETL processes, data modeling, and data pipeline development.
  • Strong hands-on experience in Python and SQL
  • Strong experience of model development, deployment, and monitoring using Vertex AI
  • Good experience of LLM, agents and agentic AI, Agent Space and hands on RAG experience
  • Experience with cloud computing concepts, including infrastructure as code (IaC), scalability, security, and cost optimization.


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