Senior Sensor Simulation Engineer, Radar

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Parallel Domain

WebsiteLinkedInAll Job Openings

51 - 200 employees

🤖 Artificial Intelligence

🔌 API

🚘 Automotive

💰 $30M Series B on 2022-11

Artificial Intelligence • API • Automotive

Parallel Domain is a company that offers an API for machine learning, computer vision, and perception teams to generate high-fidelity synthetic sensor data, including camera, lidar, and radar data. This data helps in training and testing perception models by simulating scenarios in procedurally generated worlds or replicas of any real-world location. The platform provides high-quality synthetic data to analyze, train, evaluate, and monitor perception models, enhancing AI reliability while reducing risks, development time, and costs. Parallel Domain supports various perception use cases across multiple industries, such as automotive and drones, by offering diverse datasets with edge cases and accurate annotations, thereby boosting machine learning model performance for tasks like emergency vehicle detection and traffic light classification systems.

📋 Description

• Own the multi-quarter technical roadmap for radar, lidar, and thermal modeling. • Build physically accurate sensor models focusing on radar. • Define the metrics and methodology that quantify how close our output is to measured reality. • Model the effects of weather and environmental conditions on sensor fidelity. • Extend the validation discipline across the sensor suite, camera included. • Work with perception and ML teams to translate real-world perception failure modes into prioritized fidelity requirements. • Provide technical direction to the engineers working in this area.

🎯 Requirements

• A track record of building simulation, sensor-modeling, or computational-physics software that was actually deployed and relied upon. • Strong grounding in physics, applied physics, or electrical engineering. • Radar signal processing, automotive or industrial radar domain experience, or a closely adjacent RF/electromagnetics background. • Deep grounding in the physics of one or more sensing modalities — radar/RF, lidar, thermal/infrared, or electro-optical. • Demonstrated experience validating models against real measured sensor data and reasoning carefully about accuracy, error, and what a discrepancy is actually telling you. • Must be genuinely effective at writing, debugging, and extending performance-sensitive code in modern C++. • Ability to set direction, not just execute it. • Comfortable moving between a physics discussion, an implementation discussion, and a roadmap discussion.

🏖️ Benefits

• Equity • Employer-paid supplemental medical, mental health, dental, and vision benefits • Flexible paid vacation, sick time, winter shutdown, and 11+ holidays per year • Paid parental leave • Equipment budget to optimize your setup • Annual learning and development stipend