Data annotation specialist Offres d'emploi - Ghent

Who we are

OTIV is a Ghent-based company leading the autonomous revolution in rail. We are on a mission to increase safety and efficiency of railway operations by teaching rail vehicles to drive autonomously. By making trains more efficient and safer, we actively contribute to a modal shift and a greener future. We bring this vision to life by a unique focus on the most challenging environments such as cities, shunting yards and industrial sites. Thanks to high-profile partners and world-leading clients such as Deutsche Bahn, SNCF Group, ArcelorMittal and CAF we deliver the future of railway operations today.

OTIV  is an equal opportunity employer. We are committed to a work environment that supports, inspires, and respects all individuals and in which personnel processes are merit-based and applied without discrimination on the basis of race, color, religion, sex, sexual orientation, gender identity, marital status, age, disability, national or ethnic origin, military service status, citizenship, or other protected characteristic. OTIV strives to create an environment in which all employees feel confident in their ability to bring their authentic selves to work and secure collaborating with colleagues and customers.

What you will do

As an ML engineering intern, you will research, train and validate neural networks operating on camera images or 3D point clouds. You will contribute to the main AI component of ADAS or fully self-driving systems. Since these models are trained on OTIV’s own dataset, you will be responsible for maintaining the datasets used for training and validating models.

• Research & selection of neural networks for a variety of tasks : object detection, rail detection, etc..
• Training & validation of the selected models
• Create, organize and take ownership of datasets used for training and validation
• Supervise third party annotation teams
• Closely collaborate with data engineers and robotics engineers

Requirements

Who you are

Benefits