Senior Machine Learning Engineer, Perception

Plus

. Design, implement, and optimize BEV-based perception models that fuse camera, LiDAR, and radar inputs .

Posted 10/15/2026full-timeSanta Clara • California • United StatesSenior💰 $150,000 - $200,000 per yearWebsite

Core Competencies

Role fit

Core Competencies

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Demonstrates expertise in designing and optimizing perception models for autonomous driving, with a strong focus on multimodal sensor fusion, deep learning, and real-world application deployment. Proficient in Python and experienced in leveraging frameworks like PyTorch and TensorFlow for developing robust perception algorithms.

Highest-signal resume keywords

Ph.D. Or Masters In AI, Computer Science, Electrical Engineering, RoboticsProficiency In PythonExpertise In PyTorch, TensorFlow, Or JAXExperience With LiDAR-Based 3D PerceptionDeep Understanding Of Multimodal Sensor Fusion

ATS Keywords

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Applicant Tracking System Keywords

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Hard Skills

Deep Learning3D GeometryComputer VisionPerception AlgorithmsSensor FusionModel OptimizationQuantitative MetricsBenchmarkingDistributed TrainingGPU Acceleration

Soft Skills

CollaborationContinuous ImprovementQuality Management

Tools & Technologies

LiDARCameraRadarDeep Learning PipelinesHigh-Performance Computing

Industry Keywords

Autonomous Vehicle PerceptionRoboticsProduction EnvironmentsMultimodal Sensor IntegrationQuality Management System

Tech Stack

Tools & technologies

PythonPyTorchTensorflow

About the role

Key responsibilities & impact

Design, implement, and optimize BEV-based perception models that fuse camera, LiDAR, and radar inputs
Benchmark perception models using large-scale datasets and well-defined quantitative metrics
Collaborate cross-functionally with research, data, and deployment engineers to refine models and support real-world applications
Maintain a strong focus on performance, robustness, and scalability for deployment in production systems
Ensure that your work is performed in accordance with the company’s Quality Management System (QMS) requirements and contribute to continuous improvement efforts
Ensure team compliance with QMS, monitor quality, and drive process improvements
Design scalable perception algorithms integrating camera, LiDAR, and radar data to support autonomous driving and 3D scene understanding

Requirements

What you’ll need

Ph.D. or Masters in AI, Computer Science, Electrical Engineering, Robotics, or a related field
Ph.D. new grad or Masters + 3 years industry experience
Proficiency in Python and experience building deep learning pipelines
Strong expertise in PyTorch, TensorFlow, or JAX
Proven experience with LiDAR-based 3D perception and BEV representation models
Deep understanding of multimodal sensor fusion architectures and techniques
Familiarity with camera, LiDAR, and radar modalities and their synchronization, calibration, and integration in perception pipelines
Solid foundation in computer vision, deep learning, and 3D geometry
Industry or academic experience in autonomous vehicle perception, robotics, or related areas
Hands-on experience developing deep learning models in real-world or production environments
Experience with distributed training, high-performance computing, or GPU acceleration

Benefits

Comp & perks

Work, learn and grow in a highly future-oriented, innovative and dynamic field
Wide range of opportunities for personal and professional development
Catered free lunch
Unlimited snacks and beverages
Highly competitive salary and benefits package
401(k) plan