AI Architect
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Job Location:
Monthly Salary:
Posted on:
3 hours ago
Vacancies:
1 Vacancy
Job Summary
AI/ML & Advanced Analytics
Develop train and optimize ML models using Python PySpark MLflow and Databricks Machine Learning.
Conduct exploratory data analysis (EDA) to identify patterns trends and insights in large datasets.
Deploy ML models into production using MLflow Databricks Workflows or other MLOps pipelines.
Build analytics solutions such as forecasting anomaly detection segmentation or recommendation systems.
Design ML architectures aligned with Databricks Lakehouse on Azure.
Data Engineering & Lakehouse Architecture
Architect and build scalable ETL/ELT pipelines using PySpark SQL and Databricks Workflows.
Implement Delta Lake best practices including OPTIMIZE ZORDER partitioning and schema evolution.
Design lakehouse layers (Bronze/Silver/Gold) with strong separation of compute and serving layers.
Optimize cluster performance and jobs using Spark tuning caching and shuffle minimization.
Work with multi-terabyte time-series highvelocity data in a distributed environment.
Ensure robust data availability for downstream ML and analytics workloads.
AWS Cloud Integration
Architect end-to-end data and ML solutions using Azure services including:
S3 for storage
IAM for identity & access
Glue Catalog for metadata management
Networking for secure highthroughput data movement
Integrate Databricks with AWS-native compute API layers and low-latency endpoints.
Business Collaboration & Leadership
Translate business problems into scalable analytical or ML architectures.
Communicate complex statistical and architectural concepts to nontechnical stakeholders.
Collaborate with product engineering and business leaders to drive data-informed initiatives.
Provide design leadership while remaining hands-on in execution.
