Computer Vision & AI Engineer voor Onbemande Systemen

Linear Logic B.V.; Amsterdam; On-site; EUR 70,000 - 110,000; Full time

Job summary

Linear Logic B.V. is seeking a skilled computer vision/AI engineer to advance UAV perception systems from research to field-ready deployment. You will develop, train, and optimize CV and DL models for edge hardware, balancing accuracy with latency and power constraints.

You will collaborate with software, hardware, UAV, and product teams to test and deploy new AI capabilities, ensuring robust performance in real-world environments.

Qualifications

• MSc in Computer Science, AI, ML, Robotics or equivalent experience.
• Hands-on experience developing and deploying computer vision or deep learning models.
• Strong Python programming and software development skills.
• Experience with PyTorch and edge AI platforms is a plus.

Responsibilities

• Research and adapt state-of-the-art computer vision and deep learning architectures.
• Train and evaluate models using large-scale image and sensor datasets.
• Optimise models for real-time inference on edge hardware.
• Design experiments and benchmarks to evaluate real-world performance.
• Develop data and automated annotation pipelines.
• Deploy and integrate AI models into UAV and autonomous systems.
• Analyse performance and identify opportunities for improvement with the engineering team.

Skills

Python

PyTorch

Computer Vision

Deep Learning

Edge AI

Git

Education

MSc in Computer Science / AI / ML / Robotics

Equivalent experience

Tools

NVIDIA Jetson

C++

ROS

Git

Job description

About Linear Logic

Linear Logic is an innovative scale‑up developing high‑tech UAV solutions, autonomous systems, and location intelligence. Based at Startup Village in Amsterdam, we combine AI, computer vision, geospatial technology, and unmanned platforms to develop systems for demanding real‑world environments.

The Role

You will develop computer vision models that enable UAVs to perceive and understand their surroundings, including object detection, recognition, classification, and tracking.

A key part of the role is taking AI from development to real‑world deployment. You will optimise models for edge hardware where compute resources, power consumption, latency, and environmental conditions create practical constraints.

You will work closely with our software, hardware, UAV, and product teams to develop, test, and deploy new AI capabilities.

Key Responsibilities

• Research and adapt state‑of‑the‑art computer vision and deep learning architectures.
• Train and evaluate models using large‑scale image and sensor datasets.
• Optimise models for real‑time inference on edge hardware.
• Design experiments and benchmarks to evaluate real‑world performance.
• Develop data and automated annotation pipelines.
• Deploy and integrate AI models into UAV and autonomous systems.
• Analyse performance and identify opportunities for improvement together with the engineering team.

You Should Apply If You

• Hold an MSc in Computer Science, AI, Machine Learning, Robotics, or a related field, or have equivalent experience.
• Have hands‑on experience developing and deploying computer vision or deep learning models.
• Have strong Python and software engineering skills.
• Have experience with frameworks such as PyTorch.
• Understand modern convolutional and transformer‑based vision architectures.
• Understand the trade‑offs between accuracy, latency, memory usage, and compute performance.
• Have experience with Git and collaborative software development.
• Are interested in applying cutting‑edge research to real‑world systems.

Nice to Have

• PhD in Computer Vision, Machine Learning, Robotics, or a related field.
• Experience with object detection, classification, or single/multi‑object tracking.
• NVIDIA Jetson or similar edge AI platforms.
• Synthetic data, simulation, or domain adaptation.
• C++ and/or Rust.
• ArduPilot and MAVLink.
• GIS and geospatial data.
• Experience with UAVs, robotics, or autonomous systems.

What We Offer

At Linear Logic, you will work directly on technology where AI, software, hardware, and unmanned systems come together. You will have the opportunity to take models from experimentation to deployment on real UAV platforms and directly influence future product capabilities.