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.

Required Algorithm Developer for Geometric Team
About the team:
You will be part of our REM (Road Experience Management) department, responsible for the automatic 3D High Definition map making process, a key technology powering our autonomous driving and advanced driver assistance systems.
This process runs large‑scale algorithmic pipelines on big‑data infrastructure and requires a deep understanding of the team level code, a good understanding of the data flow integration with the group level, along with strong technical and algorithmic capabilities.
We are seeking a geometrically‑inclined algorithm developer to solve real‑world geometric problems using signal processing, contributing directly to technologies that improve road safety.
What will your job look like:
Design, develop, and optimize geometric and signal‑processing algorithms for large‑scale map creation systems.
Implement and maintain production‑level Python code within a complex, large codebase.
Analyze large datasets and build scalable solutions using scientific and big‑data tools.
Take algorithms from research and prototyping through production deployment.
Continuously research and develop new algorithmic approaches to address emerging challenges.
May explore Graph Neural Network (GNN) based approaches to complement geometric algorithms.

Required Deep Learning Algorithm Engineer | Learned-Policy Group
About the team:
Build the intelligence behind the next driving decision.
Were developing learning-based driving policies for complex, real-world
scenarios. Were looking for an engineer who can turn model ideas into reliable
algorithms that run as part of our driving systems.
Youll work across model development, training, evaluation, and integration.
Youll analyze model behavior, improve the data and training process, and work
with other teams to validate performance in simulation and on real vehicles.
This is a high-impact role with direct influence on a core part of our
driving technology and its future products.
What will your job look like?
Develop and improve deep learning models for planning, decision making, and driving behavior.
Work across the full development cycle, from research papers and
prototyping models to building data and evaluation tools, debugging
infrastructure, and supporting deployment.
Design training and evaluation workflows, including metrics for safety,
progress, comfort, interaction quality, and robustness.
Analyze model behavior and failure modes, run experiments, and use the results to improve models and data.
Collaborate with control, simulation, data, and other algorithm
teams to integrate and validate new capabilities.

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.

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.