Applied Scientist AI/ML

Opendoor

Confirmed live yesterday Low trust

Quick summary

Work type
On-site
Location
—
Salary
$156,800–$355,000 / yr
Posted
176 days ago
Freshness
Confirmed live yesterday

Market check

Salary context

Above market

How this pay compares to similar roles

Similar $215k
This role $256k
$128k $379k
below market most similar roles pay here above market

This role pays more than 85% of similar roles. Most pay $177,250–$251,925 — the blue band above. At the midpoint, this role pays about $256k versus about $215k 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 21 open roles on FindRole.

Listed pay typically runs $156,800–$335,000 across 6 roles with salary data.

Most-posted roles

View all roles at Opendoor

At a glance

TL;DR · Applied Scientist AI/ML

Role Posting Log in to save

The Applied Scientist AI/ML joins a small, nimble team to push the boundaries of applied machine learning and artificial intelligence. This role focuses on developing and deploying end-to-end machine learning models, specifically designing architectural improvements for deep neural network-based home valuation models. You will build interpretable models to explain pricing decisions and incorporate unstructured data like images, videos, and text into forecasting pipelines. Key responsibilities include improving feature engineering, enhancing human-in-the-loop pricing systems, and rethinking risk and optimization models. Required skills include Python, production coding, deep learning architectures like ConvNets and Transformers, and a foundation in statistics and experimental design. Preferred experience includes Pyspark, distributed data processing, large language models, vision-language models, and background in search, recommendation systems, or personalization within the real estate domain.

What does a Applied Scientist earn?

Median $208800 from 61 postings across 10 companies.

See salary data

Skills

Python Machine Learning Deep Learning Large Language Models Vision-Language Models Pyspark Transformers ConvNets Distributed Data Processing DNN Feature Engineering Statistics Experimental Design Production Systems Search Recommendation Systems

What you'll do

  • Design and deploy architectural improvements to deep neural network-based home valuation models.
  • Build interpretable machine learning models to explain pricing decisions to customers.
  • Incorporate unstructured data like images, videos, and text into forecasting and valuation pipelines.
  • Enhance human-in-the-loop pricing systems in collaboration with Engineering and Ops teams.
  • Improve feature engineering and model training pipelines for production systems.
  • Develop and rethink risk and optimization models using real-world data and domain insights.
  • Deploy end-to-end ML models from initial research and prototyping to production implementation.

What we're looking for

  • Strong software engineering and coding skills in Python with experience contributing to production codebases.
  • Experience developing and deploying ML models end-to-end from research and prototyping to production systems.
  • Hands-on experience with deep learning architectures, including ConvNets, Transformers, or similar.
  • Advanced degree (MS or PhD) in computer science, statistics, mathematics, or a related quantitative field.
  • Solid foundation in statistics and experimental design.
  • Strong communication and collaboration skills to work with cross-functional stakeholders and communicate technical ideas clearly.
  • Familiarity with Pyspark and distributed data processing (preferred).
  • Background in search, recommendation systems, or personalization (preferred).

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