Machine Learning & Data Platform Engineer
RealPage, Inc.3 months ago
Richardson, TX, USAStaff+
Base Salary
$107k - $183k/yr
Responsibilities
- Build, train, deploy, and improve ML classification and document-understanding models for financial field and table mapping.
- Maintain and extend configuration-driven orchestration pipelines that ingest files, execute dynamic processing logic, and produce standardized outputs.
- Evolve an ETL parsing engine for complex Excel workbooks, accounting formats, and semi-structured financial data.
- Improve prediction accuracy, audit logging, processing integrity, and production reliability across clients and document types.
- Drive architecture for model serving, database schemas, API integrations, and multi-environment deployments.
- Triage bugs, ship features, make independent technical decisions, and mentor one direct report or junior engineers.
Requirements
- At least 5 years of Python development experience with production ML systems.
- Strong NLP and text-classification experience, including training and fine-tuning transformer models for document understanding.
- Deep proficiency with pandas, NumPy, SQLAlchemy, and PostgreSQL.
- Experience building and maintaining ETL pipelines for messy, semi-structured Excel and CSV data at scale.
- Familiarity with ML model-serving platforms such as Wallaroo, SageMaker, or Vertex AI, including OAuth2-based inference APIs.
- Ability to lead technically across raw file ingestion, model inference, data processing, and API integration.
- Preferred experience in real estate finance, property management, accounting data, document parsing, OCR, intelligent document processing, SFTP workflows, Paramiko, dynamic code generation or evaluation, SSH-tunneled database connections, and team mentorship.
Benefits
- Health, dental, and vision insurance.
- Retirement savings plan with company match.
- Paid time off and holidays.
- Professional development opportunities.
- Performance-based bonus eligibility depending on the position and applicable plan.
Tech Stack
Categories
Data EngineeringML Engineering