- +2
- +6
- United States
Über
At Bot Auto, you'll work on cutting-edge autonomous technologies that directly impact how self-driving cars perceive and navigate the world. You'll collaborate with experts across AI, mapping, and robotics, shaping the next generation of intelligent mapping systems. About the Role
We are seeking a highly motivated
Machine Learning Engineer
to join our HD mapping team. The ideal candidate will develop
learning-based algorithms for online map building
in both
well-maintained road environments
and
challenging construction zones . You will leverage cutting-edge
deep learning and transformer-based architectures
to improve our real-time mapping and perception systems, which serve as the foundation for safe and scalable autonomous driving. Key Responsibilities Design, train, and deploy
deep learning models
for
lane marking and road feature detection
using camera, LiDAR, and other sensor data. Develop
transformer-based architectures
and leverage other modern deep learning techniques for spatial-temporal perception and HD map updating. Handle complex scenarios such as
poorly painted lanes
and
temporary construction areas
in
dynamic weather conditions . Collaborate with perception, localization, and planning teams to integrate learning-based map components into the autonomous driving system. Conduct data analysis, dataset curation, and annotation for model training and evaluation. Qualifications Required Have an advanced degree (Ph.D or Master's) in related fields of study: computer science, computer engineering, robotics, mathematics, and etc. In-depth knowledge and extensive experience in
deep learning ,
computer vision , and modern
transformer architectures . Hands-on experience with ML frameworks such as
PyTorch
or
TensorFlow . Solid programming skills in
Python
and preferably
C++ . Strong problem-solving skills and ability to work in a fast-paced, research-driven environment. Preferred Have a proven track record of research publications in top machine learning conferences and/or journals. Prior experience in
autonomous driving perception ,
semantic segmentation ,
online map generation , or
multi-modal sensor fusion
is highly desirable. Experience with
real-world deployment
of perception models in robotics or autonomous systems. Background in handling
large-scale datasets
and
real-time processing pipelines .
Wünschenswerte Fähigkeiten
- C++
- Computer Vision
- Deep Learning
- PyTorch
- Python
- TensorFlow
Berufserfahrung
- Machine Learning
- Computer Vision
Sprachkenntnisse
- English