Senior Machine Learning Engineer
San DiegoLast seen today
Summary
Design and develop advanced machine learning models for automotive radar signal processing, including end-to-end ML pipelines from data preprocessing through model training and optimization. Evaluate novel deep learning architectures (CNNs, RNNs, Transformers) applied to radar data in time-domain, frequency-domain, and range–Doppler representations. Optimize models for real-time embedded deployment under latency, memory, and power constraints, and translate research outcomes into scalable, production-ready algorithms. Requires a Master's or PhD in a quantitative field, 3+ years of ML research experience, strong radar and signal processing fundamentals, and proficiency in Python, PyTorch/TensorFlow, and cloud platforms.
Data ScienceDevOps / InfrastructureAWSMachine LearningPythonAlgorithm ValidationApplied StatisticsClassification AlgorithmsCnnsData PreprocessingDeep LearningDetection AlgorithmsEmbedded DeploymentFeature ExtractionFrequency Domain AnalysisGoogle ColabModel TrainingModel ValidationNumpyPandasPerformance BenchmarkingPerformance OptimizationPyTorchRadar Signal ProcessingRange AngleRange DopplerReal Time DeploymentRnnsScipySignal ProcessingStatisticsTensorFlowTime Domain AnalysisTracking AlgorithmsTransformers