✦ Luna Orbit — AI & Machine Learning

Senior Applied AI Engineer – ML for Systems & Infrastructure

at Databricks

📍 San Francisco, California Unknown Posted March 10, 2026
Type Not Specified
Experience mid
Exp. Years 2-8 years
Education Not specified
Category AI & Machine Learning

This role involves applying machine learning techniques to improve system infrastructure and performance at Databricks, focusing on scalable AI models, deployment, and optimization.

  • Build end-to-end ML systems
  • Shape ML investment strategies
  • Develop scalable ML infrastructure
  • Deploy and monitor models in production
  • Contribute to open-source and research

The technical environment includes ML infrastructure, scalable systems, data storage, model training and serving, monitoring, and open-source tools, primarily within Databricks' platform.

The ideal candidate is a mid-level AI/ML engineer with 2+ years of experience in building scalable ML systems, infrastructure, and deployment pipelines. They possess strong software engineering skills and a passion for research and open-source contributions.

Machine Learning engineeringML infrastructureModel deploymentSoftware engineeringHigh velocity companies
Open-source projectsResearch publicationML modeling beyond standard librariesStatisticsMathematical modelingCluster management
DatabricksMLflowOpen-source ML libraries
Machine LearningMLAI modelsML infrastructureModel deploymentModel trainingModel servingMonitoring systemsReporting systemsSoftware engineeringOpen-sourceResearch publicationCluster managementQuery compilationOptimization algorithms
Machine LearningMLSchedulingOptimization algorithmsAI modelsML infrastructureData storageModel trainingModel servingMonitoringReporting systemsSoftware engineeringTestingCode reviewsDeploymentHigh-performance computingCluster managementQuery compilationML for SystemsResearch publicationOpen-source projects
Problem-solvingCollaborationCommunicationResearch engagementOpen-source contribution
Industry SaaS
Job Function Developing and deploying scalable AI/ML systems for infrastructure optimization
Machine LearningMLAI modelsML infrastructureModel deploymentModel trainingModel servingMonitoring systemsReporting systemsSoftware engineeringOpen-sourceResearch publicationCluster managementQuery compilationOptimization algorithmsOpen-source projects

Lack of experience in ML infrastructure, No software engineering background, Less than 2 years of relevant experience, Unwillingness to work on high-impact projects

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