Machine Learning Engineer I

Join Rocket Companies in Lewisville, TX (hybrid) and help power machine learning and data engineering systems that support real estate valuation, auction pricing, investor matching, and mortgage servicing analytics. This early-career Machine Learning Engineer I / Data Engineer I opportunity focuses on building and supporting Python-based data pipelines and Azure ML systems, including taking models from prototype through production.

Why this role

• Build end-to-end pipelines that connect ingestion, transformation, and integration across internal and external sources
• Operationalize models by supporting deployment, monitoring, and performance tracking in production
• Work within an Azure-centric stack including Azure Data Factory, Azure Blob Storage, Synapse, and a transition toward Microsoft Fabric and Purview-based governance
• Partner closely with Data Scientists to turn research code into production-ready services

Responsibilities

• Design, build, and maintain Python-based data pipelines for ingestion, transformation, and integration across internal systems (including SharePoint via Microsoft Graph API) and external sources
• Build and support ETL/ELT processes feeding the team’s Azure data environment using Azure Data Factory, Azure Blob Storage, and Synapse/Fabric
• Ensure data quality, reliability, and governance across datasets used for modeling and reporting
• Create and optimize data models, SQL queries, and workflows following the standard project structure (raw, processed, train/test data)
• Assist in deploying, monitoring, and maintaining machine learning models in production (including gradient-boosted ensembles and classification and ranking models)
• Develop data preparation and feature engineering pipelines in Python
• Support model evaluation, testing, and ongoing performance monitoring, including basic fairness/quality checks where relevant to regulated models
• Collaborate with Data Scientists to operationalize models and convert research code into production services
• Help automate model training, scoring, and deployment workflows, including containerized deployment with Docker/AKS
• Work with Data Science, Data Engineering, and business stakeholders to translate requirements into technical solutions
• Participate in code reviews, testing, and deployment activities using Git-based version control
• Document technical solutions, data dictionaries, and operational procedures clearly
• Continuously learn and adopt new AI, machine learning, and data engineering tools relevant to the Azure-centric stack
• Support the evolving Azure data platform, including transition toward Microsoft Fabric and Purview-based governance

Requirements

• Bachelor’s degree in Computer Science, Data Science, Engineering, Mathematics, or a related field
• 0–3 years of professional experience in Data Engineering, Machine Learning Engineering, Software Engineering, or a related technical field

Tools you’ll work with

Python, Azure, Microsoft Graph API, SharePoint, Azure Data Factory, Azure Blob Storage, Synapse, Fabric, SQL, Docker, AKS, Git, Microsoft Fabric, Purview

Benefits

• Eligible team members perks and health benefits
• Annual bonus, incentives, and other employment-related benefits, including medical, dental, and vision
• 401(k) retirement plan
• Paid-time off
• Reasonable accommodations

Salary: USD 112,000 - 239,000 per yearly.