Computer Vision & AI Engineer voor Onbemande Systemen
Key Skills
Job Description
Computer Vision & AI Engineer – UAV & Autonomous Systems 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. We are looking for a Computer Vision & AI Engineer to help develop the perception and autonomous capabilities of our unmanned systems. 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 Develop computer vision models for detection, classification, tracking, and scene understanding. 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. Are an EU/EEA citizen. 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. CUDA, TensorRT, ONNX, quantisation, or model compression. 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. Apply Send your CV and a short motivation letter to [email protected]. Join Linear Logic and help shape the next generation of intelligent unmanned systems.
Core Responsibilities
Develop and optimize computer vision models for UAVs, focusing on object detection, tracking, and real-time inference on edge hardware. Collaborate with cross-functional teams to integrate these AI capabilities into autonomous systems and manage data annotation pipelines.
Requirements
Requires an MSc in Computer Science, AI, Robotics, or a related field with hands-on experience in deep learning and computer vision. Candidates must possess strong Python skills and experience with frameworks like PyTorch, along with an understanding of edge hardware constraints.
About Linear Logic B.V.
Industry: Software Development
Company size: 2-10 employees
Linear Logic is a data-centric platform to manage the entire Machine Learning lifecycle. We take your unlabelled data all the way to a production ready Machine Learning model. Our core mission is to accelerate the development of Artificial Intelligence applications. The system is designed for engineers and scientists to iteratively work on their projects. Since your first idea is unlikely to be the best we must iterate to innovate. Use active learning to identify tasks that are relevant to the learning process of the model, and create more performant models with less data. Upload raw data to a project and create fully customisable workflows to structure the labelling phase. When annotating you will be supported by AI supervision tools that will reduce the annotation time by up to 90%. Bring your data, labels and model predictions together in a dataset to debug your models and identify edge-cases. Models can be trained and evaluated on a dataset in a single click, use these trained models to help you collect more data automatically! The platform allows you to create bounding boxes, named entities, relational dependencies, instance ID's, directional vectors, annotation tags and much more. Whether you work on a project by yourself or with a team, you'll be assured of radically efficient data annotations with intuitive insights into the model's performance. Try it out today at linearlogic.ai.