Staff Software Engineer

AEROVECT TECHNOLOGIES INC.
United States
1 day ago
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Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Experience level
Expert
Experience required
7 years minimum
Working hours
Regular working hours
Job source

Tech stack

Data Transformation Python (Programming Language) Object Detection Deep Learning Information Technology Lidar

Job description

  • Architect 3D object detection models, including multi-modal approaches (camera, LiDAR, Radar).
  • Build and maintain data collection and evaluation (metrics) pipeline.
  • Develop a proprietary multi-modal dataset for training and evaluation.
  • Train, deploy and monitor 2D/3D object detection models to production.
  • Build and execute a roadmap for the perception system
  • Mentor junior engineers about best practices.

Requirements

  • Master’s or PhD in Computer Science, Robotics, Deep Learning, or a related field.

  • 7+ years of focused experience in architecting and deploying 2D/3D object detection models.
  • Worked on entire perception stack (sensing, preprocessing, detection & tracking)
  • Python proficiency
  • The ability to identify gaps and lead cross functional projects

We Prefer

  • PhD in Computer Science, Robotics, or a related discipline
  • Full stack AV knowledge
  • Experience in architecting perception systems (detection & tracking)
  • Publications in major conferences like CVPR, ICRA, NeurIPS, IJCAI, AAAI etc

About the company

AeroVect is transforming ground handling with autonomy, redefining how airlines and ground service providers around the globe run day-to-day operations. We are a Series A company backed by top-tier venture capital investors in aviation and autonomous driving. Our customers include some of the world’s largest airlines and ground handling providers. For more information, visit www.aerovect.com.

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Good distractions

Talks and stories from around this role — technically off-topic, practically not.

1:19 min

Advancing autonomous driving capabilities with specialized software talent

Katrin Lehmann Katrin Lehmann +1 · Coffee With Developers

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Validating lidar sensor models against real noise

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Distinguishing artificial intelligence from deep learning

Sam Witteveen · Coffee With Developers

1:55 min

Identifying elements with the COCO-SSD object detection model

Carly Richmond Carly Richmond · World Congress 2025

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Processing physical environment data with lidar models

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Balancing data science skillings alongside systems engineering rigor

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