Machine Learning Engineer – HD Map

Bot Auto

full-time

Posted on: 10/20/2025

Location Type: Remote

Location: Remote • Texas • 🇺🇸 United States

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Mid-LevelSenior

PythonPyTorchTensorflow

About the role

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.

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.
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.

Tip: use these terms in your resume and cover letter to boost ATS matches.

deep learningcomputer visiontransformer architecturesPyTorchTensorFlowPythonC++data analysisdataset curationannotation

problem-solvingcollaborationability to work in fast-paced environment

Ph.DMaster’s