Software Engineer - ML Pricing

Opendoor•Seattle, WA

4h•$247,000 - $339,900

About The Position

Opendoor is seeking a ML Pricing Engineer to join our Engineering team in our Seattle, WA office and will play a critical role in our strategic transition to AI-powered pricing models. This high-impact, business-critical position will focus on building the scalable, production-grade platform and infrastructure necessary to support sophisticated ML models, particularly leveraging complex data sources like imagery and video.

Requirements

Extensive experience as a technical leader (Staff/Senior Staff level) in large-scale, production software and data environments.
Proven track record of designing and implementing ML/Data Platforms or Feature Stores that directly support production AI/ML models.
Deep expertise in distributed systems, cloud infrastructure, and large-scale data processing (e.g., vector search, data versioning).
Strong background in data infrastructure and API design, particularly serving data for machine learning consumption.
Experience in a domain where AI/ML is critical to the core business (e.g., pricing, optimization, recommendations).

Nice To Haves

Prior experience with computer vision pipelines or handling large-scale image/video data for ML.
Familiarity with the technical challenges of managing compute and data versioning to optimize ML iteration cycles.
Experience with agentic optimization frameworks.

Responsibilities

Platform Leadership: Lead the architecture, design, and implementation of the AI/ML feature platform, focusing on scalability, reliability, and high performance for core business systems (e.g., pricing, transaction platforms).
Feature Engineering Infrastructure: Design and build large-scale data pipelines responsible for generating, indexing, and versioning AI-derived features (predictions, embeddings) from structured and unstructured data, with a specific emphasis on image and video data.
AI Integration: Ensure seamless integration of ML capabilities into production, setting technical standards for real-time AI consumption and agentic optimization within pricing and customer-facing products.
Cross-Functional Collaboration: Partner closely with Data Science, Product, and Operations teams to translate business needs into technical requirements, ensuring the platform delivers tangible business outcomes like reduced spreads and increased transaction volume.
Mentorship & Direction: Serve as a technical mentor and leader, setting the technical direction and best practices for the new AI/ML platform group.