Description du poste
*About EasyMile*
EasyMile is a global leader in autonomous technology, powering heavy-duty driverless vehicles for airports, logistics, and industrial sites worldwide.
Since 2014, our software has driven over 1,000,000 km in 30+ countries.
We are pioneers in the industry, being the first to deploy fully driverless Level 4 solutions and holding the highest number of remotely supervised operations on the market.
*Our Mission*
We are currently focused on autonomous towing solutions, specifically our EZTow tractor and EZDolly cargo carrier.
With 150+ employees in Toulouse and Berlin, we are pushing the boundaries of LiDAR, camera, and radar integration to build a safer, more efficient future.
*Internship details*
* Duration: 6 months
* Start date: ASAP
* Location: Toulouse
* Team: Perception
* Internship subject: Deep Learning on accumulated LiDAR PointClouds
* Compensation: 1000€ gross, tickets restaurant, CSE
*Internship Context*
EasyMile is advancing Level 4 autonomous technology, allowing our vehicles to operate fully driverless in defined environments by independently managing a lot of driving situations.
Safe operation requires a high volume of environmental information, which is gathered and processed in real-time by a full range of on-board sensors like LiDAR, RADAR, and cameras.
These sensors create a complete 360-degree environmental model, capturing infrastructure, moving adverse, that the driverless system uses to make safe progression decisions.
In the Perception Team, we use deep learning techniques to analyze this surrounding environment.
Currently, our scene understanding stack runs online using few sensor scans; however, accumulating LiDAR point clouds along the vehicle’s trajectory, especially with newer sensors, allows us to represent a dense 3D scene that can significantly elevate our final performance.
This internship focuses on applying Deep Learning techniques to these large, dense PointClouds of our vehicle environment.
You will explore recent work like the Superpoint Transformer [1] and the lightweight EZ-SP [2] to help us redefine our offline perception stack, specifically aiming to improve our auto-annotation process for static obstacles, enhance the automatic creation of HD Maps, and potentially develop a new format for semantic prior maps for our autonomous vehicles.
[1] Robert, D., Raguet, H., & Landrieu, L.
(2023).
_Efficient 3D Semantic Segmentation with Superpoint Transformer_.
[2] Geist L., Landrieu L, Robert D, (2025).
_EZ-SP: Fast and Lightweight Superpoint-Based 3D Segmentation_
*Missions / Responsabilities*
Under the supervision of his tutor, the intern will be involved in:
* Format the easymile data for large pointcloud training
* Study the literature to find relevant architecture and network
* Train and evaluate such network on possible different use cases: static object detection and/or segmentation, HDMap generation
*Preferred experience*
There is no typical profile at EasyMile, we all come from different backgrounds and that is what makes us strong! Don’t hesitate to apply if you are motivated and interested by innovative transportation and technologies.
We are looking for:
* Student in computer science or machine learning or robotics
* Skills: Deep Learning, Computer Vision, Python
* Soft skills: Team spirit, autonomy, and curiosity
* Language skills : English and French
*Recruitment process*
* 30 minutes call with a recruitment team
* Meeting with the team, technical tests
* One hour interview with the tutor and a recruitment team
Type d'emploi : Stage
Durée du contrat : 6 mois
Rémunération : 1 000,00€ par mois
Question(s) de présélection:
* Merci de candidater directement sur ce lien : https://www.welcometothejungle.com/en/companies/easymile/jobs/deep-learning-on-accumulated-lidar-pointcloud-internship-toulouse_toulouse
Lieu du poste : En présentiel
Avantages:
• Titre restaurant
