{"schemaVersion":"jobsearcher.job.v1","id":"73e72b9a4d665fe73f1bb778","url":"https://jobsearcher.com/jobs/73e72b9a4d665fe73f1bb778","canonicalUrl":"https://jobsearcher.com/jobs/73e72b9a4d665fe73f1bb778","title":"Machine Learning Engineer","description":"Overview\nAs a Senior ML Engineer at Opendoor, you will build and deploy models that power pricing, risk, and decision systems in production. You’ll collaborate with researchers and analysts to turn prototypes into robust, production-ready code and systems. You’ll own end-to-end model pipelines and design mission-critical services that connect AI to real-world operations. You’ll work in a fast, high-trust environment to push AI tooling and ML lifecycle improvements at scale.\n\nResponsibilitiesBuild and train production models for pricing, automation, and decision systemsCollaborate with researchers/analysts to convert prototypes into production-grade codeOwn end-to-end model pipelines: data ingestion, training, validation, versioning, deployment, monitoringDesign and evolve mission-critical services and APIs interfacing with real-world operationsDevelop platform to accelerate the full ML lifecycle: research, retraining, experimentation, deployment, monitoringAddress real-world challenges like sparsity, data drift, and model decay in volatile marketsUtilize AI tools daily and push capabilities further in the industryLead technical design reviews, mentor teammates, and raise overall quality\nKey requirementsSenior-level or above with production ML systems experienceStrong Python fundamentalsProficiency with statistics and distributional reasoning for real-world ML monitoringEnd-to-end ML lifecycle expertise and tooling (MLflow, Airflow, Spark, Delta Lake)Ability to communicate design decisions and tradeoffs across stakeholdersBased in or willing to relocate to Miami, Toronto, or Seattlehigh agencyownership and accountabilityclear communicationPythonStatisticsML lifecycle tooling (MLflow, Airflow, Spark, Delta Lake)","company":"Opendoor","rawCompany":"opendoor","city":"Hialeah","state":"FL","isRemote":false,"isActive":false,"createdAt":"2026-09-15T04:33:21.815Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"}],"industries":[{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Machine Learning Engineer","description":"Overview\nAs a Senior ML Engineer at Opendoor, you will build and deploy models that power pricing, risk, and decision systems in production. You’ll collaborate with researchers and analysts to turn prototypes into robust, production-ready code and systems. You’ll own end-to-end model pipelines and design mission-critical services that connect AI to real-world operations. You’ll work in a fast, high-trust environment to push AI tooling and ML lifecycle improvements at scale.\n\nResponsibilitiesBuild and train production models for pricing, automation, and decision systemsCollaborate with researchers/analysts to convert prototypes into production-grade codeOwn end-to-end model pipelines: data ingestion, training, validation, versioning, deployment, monitoringDesign and evolve mission-critical services and APIs interfacing with real-world operationsDevelop platform to accelerate the full ML lifecycle: research, retraining, experimentation, deployment, monitoringAddress real-world challenges like sparsity, data drift, and model decay in volatile marketsUtilize AI tools daily and push capabilities further in the industryLead technical design reviews, mentor teammates, and raise overall quality\nKey requirementsSenior-level or above with production ML systems experienceStrong Python fundamentalsProficiency with statistics and distributional reasoning for real-world ML monitoringEnd-to-end ML lifecycle expertise and tooling (MLflow, Airflow, Spark, Delta Lake)Ability to communicate design decisions and tradeoffs across stakeholdersBased in or willing to relocate to Miami, Toronto, or Seattlehigh agencyownership and accountabilityclear communicationPythonStatisticsML lifecycle tooling (MLflow, Airflow, Spark, Delta Lake)","datePosted":"2026-09-15T04:33:21.815Z","dateModified":"2026-09-15T04:33:21.815Z","hiringOrganization":{"@type":"Organization","name":"Opendoor","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Hialeah","addressRegion":"FL","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"73e72b9a4d665fe73f1bb778"},"url":"https://jobsearcher.com/jobs/73e72b9a4d665fe73f1bb778"}}