Autonomy ML Engineer - Mapping & Perception (Remote)

Stack AV Co

New Stanton (Westmoreland County)

Remote

USD 148,000 - 232,000

Full time

23 hours ago
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Job summary

Stack AV Co is building state-of-the-art mapping and perception software for Level 4 autonomous vehicles. You will design and implement machine learning and deep learning algorithms, contribute to the team’s technical direction, and write robust real-time software for safety-critical use.

Telecommuting is allowed from anywhere in the US, with up to 25% travel. You will work on cross-functional features from problem statement to delivery, and help push the boundaries of perception systems using

Qualifications

  • Master's degree or a Bachelor's with 4+ years' experience in CS or related field.
  • Employer accepts any suitable combination of education, training, or experience.

Responsibilities

  • Deliver mapping algorithms and systems for L4 self-driving vehicles.
  • Design, develop and implement ML and DL algorithms.
  • Contribute to technical direction of the perception team.
  • Write robust software for real-time, safety-critical applications.
  • Collaborate on cross-functional features from problem to delivery.
  • Identify limitations and drive improvements to the mapping system.
  • Telecommuting permissible from any location within US; up to 25% travel.

Skills

Deep learning
Perception models
C++ programming
PyTorch
Python
Model deployment

Education

Master's degree in Computer Science or related field
Bachelor's degree in Computer Science or related field with 4+ years' experience

Tools

TensorRT
CUDA
Lidar data processing

Job description

Stack AV Co is building state-of-the-art mapping and perception software for Level 4 autonomous vehicles. You will design and implement machine learning and deep learning algorithms, contribute to the team’s technical direction, and write robust real-time software for safety-critical use.

Telecommuting is allowed from anywhere in the US, with up to 25% travel. You will work on cross-functional features from problem statement to delivery, and help push the boundaries of perception systems using

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