{"schemaVersion":"jobsearcher.job.v1","id":"b7efa595491b722be7e74975","url":"https://jobsearcher.com/jobs/b7efa595491b722be7e74975","canonicalUrl":"https://jobsearcher.com/jobs/b7efa595491b722be7e74975","title":"Machine Learning Engineer","description":"Overview\nAs a Machine Learning Engineer in Q2’s Risk & Fraud team, you will build production ML systems that detect fraud at scale, protecting trillions of dollars in transactions annually. You’ll collaborate with data scientists and engineers to turn models into real-time, reliable services and continuously improve their performance. This applied role emphasizes solving real customer problems with rigorously tested software. You’ll help shape next-generation fraud detection products and contribute to a mission-driven, collaborative culture.\n\nCompensation / BenefitsHealth & wellness benefits and competitive health insuranceHybrid work opportunitiesFlexible time offCareer development & mentoring programsParental leave for eligible new parentsCommunity volunteering and philanthropy programs\nResponsibilitiesResearch emerging fraud patterns and translate findings into new detection approachesDevelop next-generation ML products across identity, behavior, and transaction fraud with customer input to shape product directionBuild and optimize real-time, low-latency ML infrastructure for reliability, scalability, and performanceCreate and maintain data pipelines and systems for training, evaluation, and inference, productionalizing modelsWrite clean, tested code following production engineering best practices and leveraging AI toolingSupport monitoring and troubleshooting of production ML systems, including data pipelines and model performance\nKey requirementsBachelor’s degree in related field and 2+ years of relevant experienceProven experience in ML model development and deploymentStrong knowledge of statistics, optimization, probability, and experimental methodologiesProficiency in Python, R, or JavaExperience with ML frameworks/libraries (TensorFlow, PyTorch, scikit-learn)Familiarity with cloud platforms and scalable computing resourcesStrong analytical, problem-solving, and collaboration skillsAutonomy and ownership of team goalsEmpathy for end users and focus on customer value and technical qualityCuriosity about latest ML developments and practical applicationPython, R, or JavaTensorFlowPyTorch","company":"Q2 Software","rawCompany":"q2 software","city":"Raleigh","state":"NC","isRemote":false,"isActive":false,"createdAt":"2026-09-15T05:16:30.406Z","occupations":[{"code":"15-2051.00","title":"Data Scientists","slug":"data-scientists"},{"code":"15-1252.00","title":"Software Developers","slug":"software-developers"},{"code":"15-1221.00","title":"Computer and Information Research Scientists","slug":"computer-and-information-research-scientists"}],"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 Machine Learning Engineer in Q2’s Risk & Fraud team, you will build production ML systems that detect fraud at scale, protecting trillions of dollars in transactions annually. You’ll collaborate with data scientists and engineers to turn models into real-time, reliable services and continuously improve their performance. This applied role emphasizes solving real customer problems with rigorously tested software. You’ll help shape next-generation fraud detection products and contribute to a mission-driven, collaborative culture.\n\nCompensation / BenefitsHealth & wellness benefits and competitive health insuranceHybrid work opportunitiesFlexible time offCareer development & mentoring programsParental leave for eligible new parentsCommunity volunteering and philanthropy programs\nResponsibilitiesResearch emerging fraud patterns and translate findings into new detection approachesDevelop next-generation ML products across identity, behavior, and transaction fraud with customer input to shape product directionBuild and optimize real-time, low-latency ML infrastructure for reliability, scalability, and performanceCreate and maintain data pipelines and systems for training, evaluation, and inference, productionalizing modelsWrite clean, tested code following production engineering best practices and leveraging AI toolingSupport monitoring and troubleshooting of production ML systems, including data pipelines and model performance\nKey requirementsBachelor’s degree in related field and 2+ years of relevant experienceProven experience in ML model development and deploymentStrong knowledge of statistics, optimization, probability, and experimental methodologiesProficiency in Python, R, or JavaExperience with ML frameworks/libraries (TensorFlow, PyTorch, scikit-learn)Familiarity with cloud platforms and scalable computing resourcesStrong analytical, problem-solving, and collaboration skillsAutonomy and ownership of team goalsEmpathy for end users and focus on customer value and technical qualityCuriosity about latest ML developments and practical applicationPython, R, or JavaTensorFlowPyTorch","datePosted":"2026-09-15T05:16:30.406Z","dateModified":"2026-09-15T05:16:30.406Z","hiringOrganization":{"@type":"Organization","name":"Q2 Software","sameAs":"https://jobsearcher.com"},"jobLocation":{"@type":"Place","address":{"@type":"PostalAddress","addressLocality":"Raleigh","addressRegion":"NC","addressCountry":"US"}},"identifier":{"@type":"PropertyValue","name":"JobSearcher","value":"b7efa595491b722be7e74975"},"url":"https://jobsearcher.com/jobs/b7efa595491b722be7e74975"}}