Senior AI/ML Engineer

Siritech Solutions Corp

  • Austin, TX
  • 30+ days ago

    Highlights

    The ideal candidate will possess strong expertise in Azure AI/ML technologies, anomaly detection, machine learning pipelines, cloud-native data engineering, automated validation frameworks, and model monitoring within regulated government or financial environments. The consultant will be responsible for designing, developing, deploying, and maintaining AI-driven automation and data reconciliation solutions that improve data quality, accelerate migration efforts, and reduce manual validation processes.

    Numbers & Facts

    LocationAustin, TX

    Description

    Senior AI/ML Engineer:

    Total Required Experience in Years:15%2B Years

    Mode of Work:Remote / Hybrid Austin, Texas

    Seeking an experienced Senior AI/ML Engineer to support a large-scale enterprise data modernization and migration initiative. The consultant will be responsible for designing, developing, deploying, and maintaining AI-driven automation and data reconciliation solutions that improve data quality, accelerate migration efforts, and reduce manual validation processes.

    The ideal candidate will possess strong expertise in Azure AI/ML technologies, anomaly detection, machine learning pipelines, cloud-native data engineering, automated validation frameworks, and model monitoring within regulated government or financial environments.

    Key Responsibilities:

    • Design and deploy AI/ML solutions for enterprise data migration and reconciliation programs.

    • Build anomaly detection, exception classification, and root-cause analysis models.

    • Develop AI-assisted data mapping and validation automation tools.

    • Create automated reconciliation workflows eliminating manual validation activities.

    • Design and maintain Azure Machine Learning pipelines and deployment frameworks.

    • Develop cloud-native data ingestion and processing solutions.

    • Build automated validation rules and exception management frameworks.

    • Collaborate with business stakeholders to translate requirements into AI-driven solutions.

    • Develop dashboards and reporting solutions for executive-level insights.

    • Monitor model performance, accuracy, drift, and operational effectiveness.

    • Implement MLflow tracking and model lifecycle management processes.

    • Design data lineage, governance, and auditability frameworks.

    • Support CI/CD automation for AI/ML and data engineering workloads.

    • Mentor technical team members and provide knowledge transfer.

    • Ensure compliance with governance, security, and regulatory requirements.

    Required Skills:

    • Azure Machine Learning

    • Azure Databricks

    • Azure Data Factory (ADF)

    • Azure Synapse Analytics

    • Delta Lake

    • PyTorch

    • Scikit-learn

    • AI/ML Model Development

    • Anomaly Detection

    • Root Cause Analysis

    • Exception Classification

    • Data Reconciliation

    • Machine Learning Pipelines

    • MLOps

    • MLflow

    • Azure Monitor

    • Model Drift Detection

    • Azure Purview

    • Azure Functions

    • Azure Service Bus

    • Docker

    • Azure Kubernetes Service (AKS)

    • Git-Based CI/CD

    • Data Lineage Management

    Secondary Skills:

    • T-SQL

    • PL/SQL

    • SQL Server

    • Oracle Database

    • Query Optimization

    • Stored Procedures

    • Partition Switching

    • Columnstore Indexing

    • Dashboard Development

    • Agile Methodologies

    • Requirements Analysis

    • Technical Leadership

    • Stakeholder Management

    Required Qualifications:

    • 6%2B years of AI/ML pipeline development and deployment experience.

    • 6%2B years of Azure data platform engineering experience.

    • 10%2B years of advanced SQL Server and Oracle database development experience.

    • 6%2B years of experience developing automated exception classification and validation frameworks.

    • 4%2B years of cloud-native data ingestion and microservices development experience.

    • 4%2B years of model monitoring, drift detection, and ML lifecycle management experience.

    • Experience working within regulated government, financial, pension, or enterprise environments.

    • Experience translating business controls and validation requirements into automated AI-driven workflows.

    Preferred Qualifications:

    • Experience supporting pension modernization programs.

    • Experience with large-scale enterprise data migration initiatives.

    • Experience with regulated financial services environments.

    • Experience building explainable AI and governance-focused AI solutions.

    • Experience supporting executive reporting and operational analytics.

    • Experience mentoring AI/ML engineering teams.

    Deliverables:

    • AI/ML Models

    • Anomaly Detection Frameworks

    • Data Reconciliation Pipelines

    • Exception Classification Engines

    • Automated Validation Workflows

    • Azure ML Pipelines

    • Model Monitoring Dashboards

    • Drift Detection Reports

    • Data Lineage Documentation

    • Technical Design Documents

    • Executive Reporting Dashboards

    • CI/CD Deployment Pipelines

    • Knowledge Transfer Documentation

    • Operational Runbooks

    Education:

    • Bachelors Degree in Computer Science, Data Science, Artificial Intelligence, Engineering, Information Systems, or related field (or equivalent experience).