Data Architect

Veridian Tech Solutions, Inc.; United States; On-site; USD 180,000 - 240,000; Full time

Job summary

Veridian Tech Solutions, Inc. is seeking a senior AI/ML Architect to design and govern end-to-end AI/ML solutions on Azure and Databricks. You will lead technical design sessions, mentor teams, and translate business problems into scalable models.

You will optimize data pipelines with Spark/Delta Lake, implement MLOps pipelines, ensure data privacy and security, and collaborate with data scientists, engineers, and stakeholders to deliver trusted AI solutions.

Qualifications

• Extensive experience architecting AI/ML solutions at scale on Azure and Databricks.
• Deep hands-on expertise with Spark, Delta Lake, and MLflow in production.
• Proficient in Python and SQL; strong background in ML frameworks (TensorFlow, PyTorch, Scikit-learn).
• Solid experience with MLOps: CI/CD, model versioning, monitoring, retraining and governance.
• Strong data-architecture knowledge including feature stores and real-time inference.
• Experience with containerization (Docker, Kubernetes) and API development for model serving.

Responsibilities

• Architect end-to-end AI/ML solutions using Azure services and Databricks.
• Lead technical design sessions and mentor junior architects and engineers.
• Collaborate with data scientists, engineers, and business stakeholders to translate problems into scalable AI solutions.
• Design and implement MLOps pipelines for training, deployment, monitoring, and governance.
• Optimize data pipelines and feature engineering using Spark and Delta Lake.
• Ensure data privacy, security, and governance compliance.
• Evaluate emerging AI technologies and guide adoption.

Skills

Databricks

Spark

Delta Lake

MLflow

Notebooks

Model orchestration

Python

SQL

TensorFlow

PyTorch

Scikit-learn

CI/CD

Model versioning

Monitoring

Retraining

Data architecture

Feature stores

Real-time inference

Docker

Kubernetes

API development

Azure

Azure ML

Synapse

Data Lake

Tools

Azure certifications

Job description

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 skills.

Azure certifications (e.g., Azure AI Engineer Associate, Azure Solutions Architect Expert) are a plus.

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 frameworks.

Provide technical leadership and mentorship to junior architects and engineers.