{"schemaVersion":"jobsearcher.job.v1","id":"0bcb3d3af079ee86c2a99fa0","url":"https://jobsearcher.com/jobs/0bcb3d3af079ee86c2a99fa0","canonicalUrl":"https://jobsearcher.com/jobs/0bcb3d3af079ee86c2a99fa0","title":"Machine Learning Engineer","description":"We’re looking for a Machine Learning Engineer to build and deploy production-grade AI systems. In this role, you’ll take models from research to real-world applications, designing, optimizing, and scaling systems that power critical workflows across the enterprise.You’ll work closely with research, product, and engineering teams to turn cutting-edge capabilities into reliable, high-performance systems in production.Key ResponsibilitiesModel Development & Deployment: Build, fine-tune, and deploy machine learning models into production environmentsSystems Engineering: Design scalable pipelines for training, inference, evaluation, and monitoringPerformance Optimization: Improve latency, throughput, cost efficiency, and reliability of ML systemsData & Infrastructure: Work with large-scale datasets and integrate models with internal systems and APIsCross-Functional Collaboration: Partner with product and engineering teams to deliver end-to-end AI featuresEvaluation & Monitoring: Implement robust evaluation frameworks, observability, and feedback loopsMinimum QualificationsEducation: Bachelor’s or Master’s in Computer Science, Engineering, or related field (PhD optional, not required)Technical Skills: Strong proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, JAX)Production Experience: Experience deploying and maintaining ML systems in production environmentsSystems Knowledge: Familiarity with distributed systems, data pipelines, and cloud infrastructure (e.g., AWS, GCP)Practical ML Expertise: Experience with model training, fine-tuning, evaluation, and iteration at scale","company":"Eragon","rawCompany":"eragon","city":"Millbrae","state":"CA","isRemote":false,"isActive":false,"createdAt":"2026-07-18T13:35:33.946Z","occupations":[{"code":"15-1299.08","title":"Computer Systems Engineers/Architects","slug":"computer-systems-engineers-architects"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"}],"industries":[{"code":"541512","title":"Computer Systems Design Services","slug":"computer-systems-design-services"},{"code":"541511","title":"Custom Computer Programming Services","slug":"custom-computer-programming-services"},{"code":"513210","title":"Software Publishers","slug":"software-publishers"}],"jobPosting":{"@context":"https://schema.org","@type":"JobPosting","title":"Machine Learning Engineer","description":"We’re looking for a Machine Learning Engineer to build and deploy production-grade AI systems. In this role, you’ll take models from research to real-world applications, designing, optimizing, and scaling systems that power critical workflows across the enterprise.You’ll work closely with research, product, and engineering teams to turn cutting-edge capabilities into reliable, high-performance systems in production.Key ResponsibilitiesModel Development & Deployment: Build, fine-tune, and deploy machine learning models into production environmentsSystems Engineering: Design scalable pipelines for training, inference, evaluation, and monitoringPerformance Optimization: Improve latency, throughput, cost efficiency, and reliability of ML systemsData & Infrastructure: Work with large-scale datasets and integrate models with internal systems and APIsCross-Functional Collaboration: Partner with product and engineering teams to deliver end-to-end AI featuresEvaluation & Monitoring: Implement robust evaluation frameworks, observability, and feedback loopsMinimum QualificationsEducation: Bachelor’s or Master’s in Computer Science, Engineering, or related field (PhD optional, not required)Technical Skills: Strong proficiency in Python and modern ML frameworks (e.g., PyTorch, TensorFlow, JAX)Production Experience: Experience deploying and maintaining ML systems in production environmentsSystems Knowledge: Familiarity with distributed systems, data pipelines, and cloud infrastructure (e.g., AWS, GCP)Practical ML Expertise: Experience with model training, fine-tuning, evaluation, and iteration at scale","datePosted":"2026-07-18T13:35:33.946Z","dateModified":"2026-07-18T13:35:33.946Z","hiringOrganization":{"@type":"Organization","name":"Eragon","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Millbrae","addressRegion":"CA","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"0bcb3d3af079ee86c2a99fa0"},"url":"https://jobsearcher.com/jobs/0bcb3d3af079ee86c2a99fa0"}}