Software Engineer - ML Pricing

United States

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Not SpecifiedCompensation

Mid-level (3 to 4 years)Experience Level

Full TimeJob Type

UnknownVisa

Real Estate, BiotechnologyIndustries

Requirements

Candidates should have 2-4 years of software engineering experience, ideally with exposure to machine learning workflows. Proficiency in Python is essential, and familiarity with ML tools like PyTorch, scikit-learn, and MLflow is preferred. Experience with data pipelines, model training, production environments, and monitoring model performance in business-critical applications is also desired.

Responsibilities

The Software Engineer will collaborate with researchers and analysts to develop and productionize machine learning pricing models. This includes owning and operating end-to-end model pipelines, such as training, validation, deployment, and monitoring. Responsibilities also involve contributing to ML infrastructure, supporting daily model operations, addressing challenges like data drift, and driving engineering best practices within the ML codebase.

Skills

Python

PyTorch

scikit-learn

MLflow

Databricks

Spark

Delta Lake

Airflow

AWS

Machine Learning

MLOps

Data Pipelines

Model Deployment

Model Monitoring

Data Drift

Model Decay

Software Engineering

Production Code

Testing

Scalability

Opendoor

Technology-driven platform for buying and selling homes

About Opendoor

Opendoor simplifies the buying and selling of homes in the U.S. residential real estate market. For sellers, it offers a quick process where they can request a cash offer by providing property details. Using proprietary algorithms and market data, Opendoor generates a competitive offer, allowing sellers to avoid the traditional listing and negotiation hassles. For buyers, Opendoor provides a platform to browse homes and schedule self-guided tours, with the option to use their own agents. The company earns revenue through service fees from sellers and potential appreciation from homes it buys and resells. Opendoor's goal is to make real estate transactions more efficient and less stressful, while expanding its market presence and ensuring client safety.

San Francisco, CaliforniaHeadquarters

2014Year Founded

$2,023.2MTotal Funding

IPOCompany Stage

Data & Analytics, Real EstateIndustries

1,001-5,000Employees

Benefits

Happier workdays - Add a little fun to your workday with Pendo board game night, team karaoke, ping pong, or enjoy a local brew on our rooftop deck.

Health and wellness benefits - Generous health and wellness plans designed to meet the needs of you and your family, including medical, dental, and vision benefits.

Paid parental leave - Up to 16 weeks of paid parental leave, and a flexible schedule upon your return to help you make the most of those special moments.

Learning and development - In-house management development classes, guest speaker lunch and learns, and select conferences help keep talent sharp.

Flexible work hours and PTO - Enjoy the benefits of a flexible time off policy, flexible work hours, and paid parental leave.

Global offices - Work across the globe in the cities that we love like Raleigh, San Francisco, New York, Herzliya, Tokyo, London and Sheffield.

Risks

Increased competition from tech-driven traditional real estate firms may erode market share.

Recent layoffs could impact operational efficiency and service quality.

Strategic shifts from new executive appointments may not align with market demands.

Differentiation

Opendoor offers a seamless, quick, and transparent home buying and selling experience.

The company uses proprietary algorithms to provide competitive cash offers to sellers.

Opendoor's user-friendly platform allows self-guided home tours and online purchase completion.

Upsides

Growing consumer preference for digital transactions aligns with Opendoor's online platform.

AI-driven predictive analytics can enhance Opendoor's pricing algorithms for competitive offers.

Remote work trends expand Opendoor's market opportunities in suburban and rural areas.

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