ML Architect - Precision Technologies : Job Details

• Detailed JD:

Responsible for designing, implementing, and managing data and machine learning solutions on Google Cloud Platform

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 GCP services like BigQuery, 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 BigQuery, Dataflow, Dataproc, Cloud Storage, pub-sub, Kubernetes Engine, and other relevant GCP 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.