Algolux is an award-winning AI software company delivering the industry’s most robust and scalable perception for all conditions, addressing both existing cameras and new designs through cloud-based tools and embedded software. The company was founded on... Backed by Real Ventures.
About the role
Work Location: For this position, we are open to hiring in Ann Arbor, MI in a hybrid capacity. We are also open to hiring Remote in the United States.
What they're looking for
- 10+ years of experience in deep learning for perception, 3D vision, and/or autonomous systems
- M.S. or Ph.D. in Computer Science, Electrical Engineering, Robotics, or related field (or equivalent practical experience)
- Proven expertise in BEV modeling, 3D scene understanding, and multi-view fusion
- Strong background in multi-modal sensor fusion, particularly integrating camera and LiDAR data
- Proficiency in Python and deep learning frameworks such as PyTorch or TensorFlow
- Experience with large-scale data pipelines, distributed training, and experiment management systems
More about this role
At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business.
A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family , we are focused solely on developing software for automated trucks to transform how the world moves freight.
Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.
Meet the Team
As a Staff Machine Learning Engineer specializing in BEV (Bird's-Eye View) and Multi-Modal Perception, you will lead the development of next-generation models that unify information across cameras, LiDAR and radar to deliver a rich spatial understanding of the driving environment. You will drive architectural innovation, large-scale model training, and data-driven improvements that directly advance the perception capabilities at the heart of Torc's autonomous driving stack. This is a technical leadership role focused on model innovation and maturity, not downstream feature integration.
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