We are looking for a Senior ML Algorithm Engineer to lead the development and optimization of machine learning models for challenging real-world problems.
In this role, you will work hands-on across the full model-development lifecycle: understanding the task, designing and adapting algorithms, building effective training strategies, analyzing data and failure modes, and improving model quality and efficiency through rigorous experimentation.
This is an algorithm-focused role for someone who enjoys getting deeply involved in the details of model training and optimization. You will not simply operate an existing training infrastructure-you will investigate open-ended problems and develop practical solutions involving model architecture, data and sample selection, training objectives, optimization methods, and evaluation
What will your job look like:
Work on the semantics of road objects, using harvested tabular data as the primary input to our algorithms - turning large-scale, real-world observations into models that capture object meaning, attributes, and behavior on the road network.
Design, implement, and optimize machine learning and deep learning algorithms for these semantic tasks, from architecture and training objectives through evaluation and efficiency.
Develop and improve end-to-end model training pipelines, from data preparation and sampling of harvested tabular datasets through training and evaluation.
Investigate model behavior, identify failure modes, and drive targeted algorithmic improvements.
Develop effective strategies for data selection, dataset composition, sampling, augmentation, loss design, and training schedules.
Lead the investigation of complex algorithmic challenges, uncover patterns in data and model behavior, and translate insights into measurable improvements.

We are looking for an experienced Deep Learning Algorithm Developer to join one of our teams developing perception technologies for autonomous driving.
Our group tackles diverse challenges - from object detection and scene understanding to 3D perception - using large-scale, real-world in-house datasets and state-of-the-art deep learning models.
What will your job look like:
Develop and train neural networks for complex perception tasks in real-world driving environments.
Design and analyze deep learning pipelines, from data to deployment.
Collaborate with algorithm, software, and data experts to deliver production-ready models.
Research and apply new methods in computer vision, 3D perception, and multi-task learning to improve performance and efficiency.

We are looking for a senior computer vision engineer: a hands on individual contributor whose work will be broad and touch many projects across the group, to lead long-term research initiatives and POCs that shape the technical direction of our technology.
What will your job look like:
Lead long-term applied research and POCs that determine the direction of our perception and autonomy technology.
Design and implement modern end-to-end perception and multi-modal learning systems across diverse vision tasks (e.g., detection and tracking, 3D reconstruction, multi-camera fusion, motion prediction).
Translate research innovations into high-quality, validated POCs designed for adoption by production teams and deployment within autonomous vehicle platforms.

Required Experienced Deep Learning Algorithm Developer
About the team:
The road algorithm team is responsible for the critical and challenging task of detecting the drivable lanes on the road. We focus on Deep Learning algorithms, classical Computer Vision and Geometric Modeling algorithms.
We are looking for an Algorithm Developer to help us advance our technology and push the boundaries of what's possible in autonomous driving.
What will your job look like:
Research and develop state-of-the-art computer vision and deep learning algorithms for ADAS and autonomous driving.
Participate in the entire development cycle, from initial research and prototyping to deployment on real-time embedded systems within the vehicle.
Collaborate with engineering and research teams in Computer Vision, Machine Learning, and Data Engineering to solve real-life problems.
Analyze large datasets to improve algorithm performance and robustness.