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Open nowPosted 3 days ago

Deep Learning Engineer (Radar Computer Vision)

robin-radar31 open roles

Where
Delft
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Hybrid
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Your applicationOpen nowDeep Learning Engineer (Radar Computer Vision)robin-radar · Delft
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7.7% of postings close within 7 days. Measured by our own scanner across the market. robin-radar postings stay open a median of 4 days.

Share of postings closed within
  1. 1.6%1 day
  2. 3.3%3 days
  3. 7.7%7 days
  4. 14.0%14 days
  5. 33.7%30 days
This job: posted 3 days ago

robin-radar median: 4 days open

The posting

Turn complex radar data into clear detections – so our software can spot birds, drones, and airborne threats in real time.

As our Deep Learning Engineer, you architect and implement object detection frameworks for non-natural radar imagery. You work side-by-side with fellow AI specialists, software engineers, and radar experts to ensure your research translates directly to edge computing hardware.

Reporting to the AI Lead, your models directly power live radar systems across the globe.

WHAT YOU'LL DO

- Framework design and architecture: Build robust detection, segmentation, and tracking models for complex 3D, 4D, and 5D radar data. Translate raw signal processing concepts into high-performing neural network architectures.

- Data strategy and label management: Develop innovative strategies to handle imperfect, sparse, or missing radar labels. Automate dataset creation and labeling workflows to keep research moving fast.

- Model optimization for the edge: Optimize neural networks using TensorRT for real-time, low-latency inference. Ensure every model runs smoothly on edge hardware deployed in the field.

- Cross-functional integration: Partner closely with software and radar engineers to integrate your models into live products. Co-develop and refine deep learning approaches alongside your AI teammates.

WHAT YOU BRING

- Master's degree in Computer Vision, Artificial Intelligence, Computer Science, or a related field

- 5+ years of professional experience in deep learning research for computer vision

- Proven expertise in object detection, segmentation, and classification models

- Deep familiarity with radar data or non-natural signal modalities like LiDAR, sonar, or medical imaging

- Hands-on experience deploying and optimizing models for edge computing hardware

- Advanced proficiency in Python and PyTorch

- Experience with TensorRT or similar high-performance inference libraries is a strong advantage

- Fluent English, both written and spoken

N.B. Don't worry if you don't tick every box. Our mission is a journey, and there's plenty to learn along the way. If most of this fits, we'd love to hear from you.

A Certificate of Conduct (VOG) and a background check are part of our screening process. We appreciate your understanding.

WHAT WE OFFER

- Working for a Great Place to Work® certified company;

- Comprehensive pension plan;

- Commuting allowance;

- 30 days of paid holiday leave (with the possibility to buy 3 additional days);

- Opportunities to develop your skills even further through training and certifications;

- High quality laptop/desktop, monitor, headphones, and any other equipment necessary for your role;

- An international team of 30+ nationalities, full of high performance colleagues you can exchange experiences with and learn from. As well as having a lot of fun in our social events and Friday drinks!

Robin Radar is a technology leader in tracking and classifying small objects. Our radars and software help prevent bird strikes in aviation, reduce the impact of wind farms on wildlife, and protect critical infrastructure from drone threats. Our work shows up at airports, wind farms, military sites and nature reserves around the world.

We're one of the top 10 fastest-growing companies in the Netherlands, with a crew of bright minds across 30+ nationalities. Growth doesn't mean we lose the plot – eyes on the skies, feet on the ground. Our values keep us grounded: WE TRUST. WE OWN IT. WE AIM HIGH.

Want to work on next-level radar tech, solve real problems, and never have to pretend your job has meaning?

You'll fit right in – we're saving you a seat.

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