About this opportunity
Gatik lists this Machine Learning Engineer Santa Clara, CA opportunity in northern, Kentucky. Review the employer’s description below for duties, qualifications and application requirements.
Job description
Weareseekingahigh-impact,technicallydeepMachineLearningEngineertodevelop,optimize,anddeployproductionMLmodelsacrossourautonomousvehicle(AV)stack.Thisroleisidealforengineerswhoenjoybuildingmodelsend-to-end-fromdataandtrainingthroughoptimizationandreal-timedeploymentonautonomousvehicles.
You will work closely with perception, prediction, planning, infrastructure, systems, and hardware teams to ensure models are efficient, scalable, reliable, and production-ready for both on-vehicle and cloud workflows.
This role is onsite 5 days a week at our Santa Clara, CA office!
Whatyou'lldo
AutonomousDrivingModels: Developandimprovemodelssupportingperception,prediction,planning,andsceneunderstanding.
EfficientNeuralNetworkDesign: Optimizemodelsusingtechniquessuchasquantization,pruning,sparsification,compression,andefficientarchitecturedesigntomeetstrictlatency,compute,memory,andpowerconstraints.
ModelOptimization: ProfileandoptimizeneuralnetworksusingCUDA,TensorRT,andrelatedtechnologies.
SimulationandEvaluation: Analyzemodelperformanceusingsimulationandreal-worlddrivingdata,identifyfailuremodes,anddriveimprovements.
ScalableMLInfrastructure: Buildhigh-throughputpipelinesfortraining,evaluation,dataprocessing,andlarge-scaleofflineinference.
DataWorkflowsandTooling: Developreliablepipelinesfordatasetcuration,annotation,preprocessing,visualization,diagnostics,benchmarking,andcontinuousfeedbackfromfielddata.
Cross-FunctionalIntegration: Partnerwithautonomy,systems,hardware,andinfrastructureteamstoensureMLcomponentsintegratereliablyintothebroadervehicleplatform.
Whatwe'relookingfor
Education: MSorPhDinComputerScience,MachineLearning,Robotics,ElectricalEngineering,Statistics,Optimization,orarelatedfield.
Experience: Opentoallexperiencelevels.Levelingwillbedeterminedbasedonexperienceandtechnicaldepth.
Programming&Frameworks:
StrongPythonskillsandexperiencewithframeworkssuchasPyTorchorTensorFlow.
CoreML&SystemsExpertise:
Experiencedeployingandoptimizingneuralnetworksforreal-time,embedded,robotics,autonomousdriving,orotherperformance-constrainedsystems.
Experiencewithmodeloptimizationtechniquessuchasquantization,pruning,compression,andefficientarchitectures.
Experiencewithsoftwarearchitecture,profiling,latencyoptimization,system-leveldebugging,anddataflowanalysis.
Infrastructure&ComputeTools:
ExperiencewithCUDAandTensorRTishighlydesirable.
Experiencewithcloud-basedMLtrainingandevaluationpipelines,preferablyAzure.
BonusQualifications:
Experiencewithtransformers,multimodalmodels,diffusionmodels,worldmodels,orend-to-enddrivingmodelsisaplus.
Experienceinautonomousdriving,robotics,orothersafety-criticalreal-timeMLsystemsisstronglypreferred.
PublicationsordemonstratedtechnicalcontributionsinefficientML,autonomousdriving,robotics,orrelatedareasareaplus.
Priorcontributionstolarge-scaleMLsystemsdeployedinproduction.
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Who can apply
Review the original listing for work authorization, qualifications and employer requirements.