✦ Luna Orbit — AI & Machine Learning

Untitled Position

at Company

Unknown Posted March 30, 2026
Type Full-Time
Experience senior
Exp. Years 8+ years
Education Bachelor's Degree
Category AI & Machine Learning

Senior Manager, Machine Learning Engineering leads ML productionization efforts at Capital One, shaping architecture, pipelines, and governance for scalable ML solutions and leading teams across product and data science.

  • Design, build, and deliver ML models and components; Inform ML infrastructure decisions; Solve complex problems with code and validation; Collaborate in cross-functional Agile teams; Retrain and monitor models in production

Requires strong coding in Python/Scala/Java, ML frameworks like PyTorch or TensorFlow, experience with cloud platforms (AWS/Azure/GCP), CI/CD, data pipelines, and responsible AI governance. Focused on production-ready ML systems and cross-functional collaboration.

The ideal candidate is a senior ML engineering leader with 8+ years building data-intensive ML systems, strong Python/Scala/Java skills, and extensive cloud experience (AWS/Azure/GCP). They can lead cross-functional teams, productionize ML at scale, and communicate complex concepts to executives.

Bachelor's Degree8+ years of experience designing and building data-intensive solutions using distributed computing4+ years of experience programming with PythonScalaor Java3+ years of experience buildingscalingand optimizing ML systems2+ years of experience leading teams developing ML solutions4+ years of people management experience
Master's or Doctoral Degree in computer scienceelectrical engineeringmathematicsor a similar field4+ years of on-the-job experience with ML frameworks such as scikit-learnPyTorchDaskSparkor TensorFlow3+ years of experience developing performantresilientand maintainable code3+ years of experience with data gathering and preparation for ML modelsExperience deploying ML solutions in AWS/Azure/GCP3+ years building production-ready data pipelines
Bachelor's Degree; distributed computing experience; Python; Scala; Java; ML frameworks (scikit-learnPyTorchDaskSparkTensorFlow); cloud platforms (AWSAzureGCP); data pipelines; model training; CI/CD; MLOps; Explainable AI; productionizing ML; leadership; communication
PythonScalaJavadistributed computingML modelsCI/CDcloud platforms AWSAzureGoogle Cloud Platformdata pipelinesPyTorchscikit-learnSparkTensorFlowDaskMLOpsExplainable AImodel governance
CommunicationLeadershipTeam collaborationProblem solvingStrategic thinking
Industry Fintech
Job Function Oversee the end-to-end ML engineering lifecycle from model development to production deployment in a scalable, governed, cloud-based environment
Role Subtype Senior ML Engineer
Tech Domains Python, Java, Scala, Google Cloud Platform, Amazon Web Services, Azure, Spark, TensorFlow, PyTorch, SQL / PostgreSQL
senior managermachine learning engineeringml engineeringmachine learningdistributed computingpythonscalajavamodel trainingci/cdcloudawsazuregoogle cloud platformdata pipelinespytorchscikit-learnsparktensorflowdaskmlopsexplainable aimodel governanceproductionizing mllead teamscommunicationrisk governancemachine learning engineerproduction MLgcp

Less than 8 years of distributed ML experience, No cloud platform experience, No leadership experience in ML teams

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