Entrylevel Retrieval Augmented Generation Jobs in Austin, TX

MLOps Engineer

DPR is a leading construction company committed to delivering high-quality, innovative projects. Our team integrates cutting-edge technologies into the construction process to streamline operations, enhance decision-making, and drive efficiency at all levels. We are looking for aMLOps Engineerto join our team and contribute to developing robust data solutionsto support our Machine Learning,Data Science, Data Engineering and Software Engineering.

Position Overview

TheMLOps Engineerwill be instrumental inthe designand implementation of scalable, cloud-nativesolutions to meet the growing needs of ourData & Developmentteam.Thesuccessful candidatewill demonstrate the abilitytoabstract complexity andcreatereusable, scalable patternsthat accelerate development.The MLOps Engineerwilldesign, build and support the infrastructureand systemsthat enable our teams to deliver reliable, high-impactdata,workflows, and collaboratingclosely with data engineers, software developers, data scientists and product teams.

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 practicesacross AI/ML and other development teamsincluding logging, metrics, tracing, and model performance monitoring, ingesting data from multiple platforms

• Design and deploy containerized MLworkloads,partnering withInfrastructureEngineering 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 withInfrastructureEngineering toautomate infrastructure provisioning

• Act as a technical point of contact forDevOps andMLOps practices,developing reusable patterns, documentation, and proof-of-concepts to drive adoption

Qualifications

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

• 5+years of experience inDevOps, MLOps,Data Engineering,Software Engineeringor Site Reliability Engineering

• Strong understanding of cloudinfrastructure and experience working with at least one major cloudprovider, preferably Azure

• Proficiencyinat least one objected-oriented programming language, preferably pythonwith hands-on experience inml frameworks like TensorFlow, PyTorch or Scikit-learn

Required Skills

• Experience with CI/CD processes and automation

• Experience withInfrastructure as Codetoolssuch as Terraform,Bicep

• Proficiencyincontainerized application deploymentsand container orchestration- experience with Kubernetes, especially AKS would be a huge plus

• Experiencestanding up and managingobservability tools such as Datadog, Azure Monitor or GrafanaforAPM, LLM Opsand model performance monitoring

• Experiencedeploying production-ready machine learning models

• Experience withModel explainability (SHAP, LIME)or similar

• Experience with cloud cost management and practices (e.g., Azure Cost Management, chargeback/show back models).

Nice to Have

• Experience in Azure, particularly AKS,ACR, ARM,App Service, Azure Machine Learning and AI Foundry, Azure Monitor

• Familiarity with semantic search, retrieval-augmented generation (RAG), or embedding pipelines

• Exposure to managing and monitoring ML workloads that support generative AI or advanced analytics use cases

• Proficiency with Snowflake

• Experience with workflow orchestration platforms such as Apache Airflow, Argo Workflow, Prefect, etc.