About this role
Build and productionize machine learning applications with an emphasis on architectural design, scalable ML systems, and operational excellence. Lead ML engineering activities across modeling, deployment automation, and ongoing monitoring while following Responsible and Explainable AI principles.
Key Responsibilities
- Design and deliver ML models and components; Inform ML infrastructure decisions (model choice, training, tuning, validation); Write and test application code and automate tests/deployment; Retrain, maintain, and monitor models in production; Build cloud-based architectures and optimized data pipelines with CI/CD
Technical Overview
Design, build, and operationalize ML models and components using Python, Scala, or Java with distributed computing. Implement CI/CD with test automation, create optimized data pipelines, and ensure continuous monitoring and retraining in production environments, including model governance and vulnerability reduction.
Ideal Candidate
The ideal candidate is a Lead Machine Learning Engineer with 8+ years designing and building data-intensive distributed computing solutions and 4+ years programming with Python, Scala, or Java. They have 3+ years building and optimizing ML systems in production, including CI/CD, test automation, data pipelines, and ongoing model retraining/monitoring, with experience supporting Responsible and Explainable AI.
Must-Have Skills
Bachelor's DegreeAt least 8 years of experience designing and building data-intensive solutions using distributed computingAt least 4 years of experience programming with PythonScalaor JavaAt least 3 years of experience buildingscalingand optimizing ML systemsAt least 2 years of experience leading teams developing ML solutionsContinuous integration and continuous deployment best practicesTest automationModel retrainingmaintenanceand monitoring in productionResponsible and Explainable AI
Nice-to-Have Skills
Master's or doctoral degree in computer scienceelectrical engineeringmathematicsor a similar fieldExperience developing and deploying ML solutions in a public cloud such as AWSAzureor Google Cloud Platform4+ years of on-the-job experience wi
Tools & Platforms
Amazon Web ServicesAWSMicrosoft AzureAzureGoogle Cloud PlatformCI/CD
Required Skills
Machine learning engineeringdistributed computingPythonScalaJavaML architectural designmodel traininghyperparameter tuningfeature selectiondimensionalitybias/variancevalidationdata pipelinesCI/CDtest automationmodel retrainingmodel monitoringResponsible and Explainable AIhigh availabilityperformance
Hard Skills
Machine learning architectural designProductionizing machine learning applicationsHigh availabilityPerformance of machine learning applicationsModel code developmentModel application code reviewModel retrainingModel monitoringWriting and testing application codeAutomating testsAutomating deploymentCI/CD best practices (continuous integration and continuous deployment)Test automationMonitoringCloud-based architecturesData pipelinesDistributed computingPythonScalaJavaHyperparameter tuningFeature selectionModel trainingDimensionalityBias/varianceValidationResponsible and Explainable AIRisk governanceReducing vulnerabilitiesAgile team collaboration
Soft Skills
CollaborationCross-functional teamworkCommunication with Product and Data Science teamsContinuous learning mindsetOwnership of production systemsAgile collaboration
Keywords for Your Resume
Senior Lead Machine Learning EngineerMachine Learning Engineer (MLE)MLEproductionizing machine learning applicationsmachine learning architectural designPythonScalaJavadistributed computingmodel traininghyperparameter tuningfeature selectiondimensionalitybias/variancevalidationdata pipelinescontinuous integrationcontinuous deploymentCI/CDtest automationmodel retrainingmodel monitoringResponsible and Explainable AIhigh availabilityperformanceAgile teamMachine Learning Engineerproductionizing machine learning
Deal Breakers
Bachelor's Degree required, At least 8 years designing and building data-intensive solutions using distributed computing, At least 4 years programming with Python, Scala, or Java, At least 3 years building, scaling, and optimizing ML systems, At least 2 years leading teams developing ML solutions
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