Data & AI Architect
Siri InfoSolutions Inc
Allentown, PA, United States
about 2 months ago
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Role details
Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Compensation
$150,000.0 - $160,000.0
Working hours
Regular working hours
Job source
Tech stack
Artificial Intelligence
Microsoft Azure
Continuous Integration
Data as a Services
Data Architecture
Data Centers
Python (Programming Language)
Machine Learning
Tensorflow
Azure Machine Learning
Azure Data Lake
SQL Databases
+17 more
Feature Engineering
Azure Data Factory
Pytorch
Apache Spark
Modularization
Containerization
Data Lakes
Scikit Learn
Kubernetes
Machine Learning Operations
Api Design
Azure Synapse Analytics
Software Version Control
Data Pipelines
Serverless Computing
Docker
Databricks
Job description
- Architect end-to-end AI/ML solutions using Azure services (Azure ML, Synapse, Data Lake, etc.) and Databricks.
- Lead technical design sessions and guide teams on best practices for scalable and secure AI solutions.
- Collaborate with data scientists, engineers, and business stakeholders to translate business problems into AI solutions.
- Design and implement MLOps pipelines for model training, deployment, monitoring, and governance.
- Optimize data pipelines and feature engineering workflows using Spark and Delta Lake on Databricks.
- Ensure compliance with data privacy, security, and governance standards.
- Evaluate and integrate emerging AI technologies and framework
- Provide technical leadership and mentorship to junior architects and engineers.
Requirements
- Strong expertise in Microsoft Azure AI & Data services: Azure Machine Learning, Azure Synapse, Azure Data Factory, Azure Data Lake, Azure Functions.
- Hands-on experience with Databricks: Spark, Delta Lake, MLflow, notebooks, and job orchestration.
- Proficiency in Python, SQL, and ML frameworks like TensorFlow, PyTorch, Scikit-learn.
- Experience with MLOps tools and practices: CI/CD, model versioning, monitoring, and retraining., * Deep understanding of data architecture, feature stores, and real-time inference.
- Familiarity with containerization (Docker, Kubernetes) and API development for model serving.
- Excellent communication and stakeholder management skill
- Azure certifications (e.g., Azure AI Engineer Associate, Azure Solutions Architect Expert) are a plus.
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