Zeitview(formerlyDroneBase)istheleadingintelligentaerialimagingcompanyforhigh-value
infrastructure,providingbusinesseswithactionable,real-timeinsightsthroughasingle-source
solutiontorecoverrevenueandreduceliabilityrisk.Zeitviewisthetrusted,go-todata
managementplatformforworldwideenterpriseclientsspanningindustriessuchasrenewable
energy,insurance,telecommunications,construction,realestate,andcriticalinfrastructure

Job Description: As an ML (Machine Learning) Engineer, you will help designanddevelopAI
computervisioninferenceinfrastructureacrossmultipleindustryverticalsincludingsolar,wind
turbines,andcommercialroofing.Thesemodelswillneedtobedeployedinbatchprocessingalong
withrealtimestreamingarchitecturesinacloudenvironment.Youwillalsohelpdesignanddevelop
modelmonitoringframeworkstoensurethedeployedmodelsarefunctioningproperly.Working
collaborativelywithproductmanagersandMLengineerswillberequiredtoensurethemodelsare
performingtotheproductspecifications.Thedaytodaydutiesofthejobwillincludebuilding,
monitoring,anddeployingmachinelearninginferencepipelinesincloudenvironmentssuchas
AmazonWebServices(AWS).Thedutieswillalsoincludeoptimizingthemachinelearninginference
pipelinestobefaster,morescalable,andmorerobust.Thispositionwillalsoconsistof
collaborating,androadmappingideaswithothermembersofthemachinelearningteamandother
crossfunctionalteams.Itwillalsobeexpectedthatthisrolewillrequireyoutowritedocumentation
onhowtorun,test,andusethevariousmodelsandotherprogramsthatyouwilldevelop

Employer’sminimumjobrequirements:
● Experiencewithdeployingcomputervisionmodelsinaprofessionalsetting
● Experiencewithdeployingandmonitoringmachinelearningmodelsintoproduction
environments
● ExperiencewithPython,Pytorch,andAWS
● Experiencebuildinghighlyscalablemachinelearningmodelsthatcanhandlelargeamounts
ofvolumeanddata
● Experienceworkingwithaerialand/orgeospatialimagery
● ExperiencewithMetaflowandPytorchLighting

MinimumDegree:BachelorsinProgress
FieldsofAcceptableStudy:ComputerEngineering,ElectricalEngineering,Statistics,Computer
Science

ML Engineer Technical Coding Challenge
● Turbine Preflagging Classifier Deployment
○ Give turbine preflagging model weights and simple inference script
○ 50 anomaly images
○ 50 clean images
○ Deploy model as endpoint locally
○ Create script to test model endpoints
○ Create model monitoring scripts
○ Create unit and integration tests for model deployment
○ Explain how you would scale your model deployment in a cloud infrastructure