Machine Learning Engineer- Platform

Opendoor

Quick summary

Work type
On-site
Location
WA
Salary
$205,000–$281,000 / yr
Posted
35 days ago

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $221k
This role $243k
$158k most similar roles pay here $294k

This role pays more than 68% of similar roles. Most pay $192,250–$249,750 — the shaded band above. At the midpoint, this role pays about $243k versus about $221k for comparable roles.

Based on 240 similar postings.

Employer

About Opendoor

Opendoor is a digital real estate marketplace that buys and sells homes directly to consumers, simplifying the home selling and buying experience through instant offers and transparent pricing. Industry: Real Estate Technology & iBuying

Opendoor currently has 36 open roles on FindRole.

Listed pay typically runs $156,800–$335,000 across 8 roles with salary data.

Most-posted roles

View all roles at Opendoor

At a glance

TL;DR · Machine Learning Engineer- Platform

Join our Seattle-based Pricing & ML team as a Senior Software Engineer ML Ops, where you will lead the design and implementation of services and workflows that enable reliable training, deployment, and monitoring of pricing and machine learning models. You’ll work closely with data scientists, ML engineers, and product managers to convert model prototypes into robust production systems, owning end-to-end operations from data ingestion to monitoring. Key responsibilities include developing Python code for production readiness, optimizing SQL queries over large datasets, and implementing automation for key ML lifecycle workflows. Ideal candidates have 8+ years of experience in software engineering or a related field, with strong proficiency in Python, SQL, and hands-on experience with ML pipelines in high-stakes environments. Familiarity with tools like MLflow, Airflow, and Delta Lake is beneficial, as is an understanding of the real estate domain’s unique challenges.

What you'll do

  • Lead the design and implementation of services and workflows for ML model production.
  • Convert model prototypes into clean, testable Python code and robust systems.
  • Own end-to-end operation of model pipelines including data ingestion and deployment.
  • Design and maintain full lifecycle workflows for experimentation and iteration.
  • Develop and optimize SQL queries over large datasets for efficient data access.
  • Implement automation for key ML lifecycle tasks like retraining and canary releases.

What we're looking for

  • 8+ years of software engineering experience or 6+ with a Master's degree in ML workflows.
  • Strong proficiency in Python, including maintainable and well-tested production code.
  • Solid experience with SQL queries, joins, indexing, and performance optimization.
  • Proven track record owning and operating data pipelines in high-stakes environments.
  • Deep familiarity with the entire ML lifecycle from training to deployment and monitoring.
  • Demonstrated ability to make technical design decisions and communicate trade-offs effectively.
  • Strong collaboration skills working closely with data scientists and cross-functional teams.

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