Machine Learning Engineer

Gatik AI; Santa Clara (CA); In loco; USD 170.000 - 240.000; Tempo pieno

Descrizione del lavoro

Gatik AI seeks a high-impact Machine Learning Engineer to develop, optimize, and deploy production ML models across our autonomous vehicle stack. You will collaborate with perception, prediction, planning, infrastructure, systems, and hardware teams to deliver scalable, real-time ML across on-vehicle and cloud workflows.

The role is onsite at our Santa Clara, CA office, requiring deep ML expertise and ownership of end-to-end model development, including data strategy, training, and deployment

Competenze

• Deep ML lifecycle experience from data prep to deployment.
• Experience in end-to-end ML development for AV or robotics.
• Strong background in model optimization and real-time inference.

Mansioni

• Own the full ML lifecycle from data strategy to deployment.
• Develop models for perception, prediction, planning, and scene understanding.
• Optimize models to meet latency, compute, memory, and power constraints.
• Integrate trained models into C++-based autonomous systems.
• Profile and optimize neural networks using CUDA and TensorRT.
• Collaborate with cross-functional teams to productionize ML components.

Conoscenze

End-to-End model development

Autonomous driving models

Efficient neural network design

Real-time deployment

Model optimization

Simulation & evaluation

Scalable ML infrastructure

Data workflows

Cross-functional integration

Formazione

MS/PhD in CS/ML/Robotics/EE/Statistics

Strumenti

CUDA

TensorRT

PyTorch

TensorFlow

C++

Python

Descrizione del lavoro

Abouttherole

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

• End-to-EndModelDevelopment: OwnthefullMLlifecycle,includingdatastrategy,preprocessing,training,evaluation,optimization,deployment,andmonitoring.
• AutonomousDrivingModels: Developandimprovemodelssupportingperception,prediction,planning,andsceneunderstanding.
• EfficientNeuralNetworkDesign: Optimizemodelsusingtechniquessuchasquantization,pruning,sparsification,compression,andefficientarchitecturedesigntomeetstrictlatency,compute,memory,andpowerconstraints.
• Real-TimeDeployment: IntegratetrainedmodelsintoC++-basedautonomysystemsandoptimizeinferenceforproductionvehiclehardware.
• 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.
• StrongC++skillsandexperienceintegratingMLmodelsintohigh-performanceproductionsystems.
• CoreML&SystemsExpertise:
• DeepunderstandingofMLworkflows,includingdatacuration,training,evaluation,ablationstudies,deployment,andinferenceoptimization.
• 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.

SalaryRange $170,000-$240,000