MLOps Engineer: AI DataOps & Cloud-Native Pipelines

DPR Construction; Tampa (FL); On-site; USD 120,000 - 170,000; Full time

Job summary

DPR Construction is seeking an experienced Data and MLOps Engineer to join our Data and AI team and collaborate with the Data Platform, BI and Enterprise Architecture groups to shape the direction of DPR’s AI initiatives.

You will work with cross-functional teams to align business needs with data architecture and define data models for focus areas, building scalable, cloud-native solutions and reusable patterns across DevOps and ML workflows.

Qualifications

• Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related field
• 5+ years of experience in DevOps, MLOps, Data Engineering, Software Engineering or Site Reliability Engineering
• Strong understanding of cloud infrastructure and experience working with at least one major cloud provider, preferably Azure
• Proficiency in at least one objected-oriented programming language, preferably python with hands-on experience in ml frameworks like TensorFlow, PyTorch or Scikit-learn

Responsibilities

• Lead hands-on implementation of automation-first DevOps and MLOps practices, enabling infrastructure-as-code and consistent, repeatable environment provisioning
• Design and manage intelligent DataOps pipelines with automated data quality monitoring and anomaly detection
• Standardize observability practices across AI/ML and other development teams including logging, metrics, tracing, and model performance monitoring, ingesting data from multiple platforms
• Design and deploy containerized ML workloads, partnering with Infrastructure Engineering for cluster provisioning and governance
• Extend existing CI/CD pipelines to support automated infrastructure changes and ML workflows
• Implement AI-driven data validation, schema drift detection, and metadata management
• Establish governance frameworks for AI systems, including bias detection, explainability, and auditability
• Extend existing Azure RBAC strategy by automating role and permission management to reduce manual intervention
• Collaborate with Infrastructure Engineering to automate infrastructure provisioning
• Act as a technical point of contact for DevOps and MLOps practices, developing reusable patterns, documentation, and proof-of-concepts to drive adoption

Skills

DevOps

MLOps

Data engineering

Software engineering

Site Reliability Engineering

Education

Bachelor’s degree in Computer Science, Data Science, Information Systems, or a related field

Tools

Terraform

Bicep

AKS

Azure Monitor

Datadog

Grafana

Snowflake

Apache Airflow

Argo Workflow

Prefect

Job description

DPR Construction is seeking an experienced Data and MLOps Engineer to join our Data and AI team and collaborate with the Data Platform, BI and Enterprise Architecture groups to shape the direction of DPR’s AI initiatives.

You will work with cross-functional teams to align business needs with data architecture and define data models for focus areas, building scalable, cloud-native solutions and reusable patterns across DevOps and ML workflows.