Wayve
Principal ML Engineer, App SW(m/w/x)
Full-timeWith HomeofficeSenior
Leonberg
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WAWayve
Machine Learning Engineer, App SW(m/w/x)
Leonberg
Full-timeWith Home OfficeSenior
AI/ML
Data Science
Nejo AI Summary
Developing end-to-end driving models and evaluation pipelines for autonomous driving AI at Embodied AI developer. Proven track record shipping production deep learning with Python/PyTorch expertise required. Direct influence on core AI architecture and training methodologies.
Requirements
- Proven track record shipping production deep learning
- Expertise in deep learning
- Proficiency in Python, C++, CUDA, and PyTorch
- Experience with real-time systems or robotics
- Ability to lead initiatives and mentor
- Prior work in autonomous driving
- Familiarity with human behavior modeling
- Experience integrating ML into production hardware
- Passion for self-driving cars
Tasks
- Develop robust end-to-end driving models
- Lead personalized and collaborative driving projects
- Build closed-loop and open-loop evaluation pipelines
- Curate real-world and synthetic data sets
- Influence architecture and training methodologies
- Collaborate cross-functionally to ensure integration velocity
- Mentor senior engineers on technical direction
Work Experience
- approx. 4 - 6 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- C++
- CUDA
- PyTorch
Benefits
Flexible Working
- Hybrid working policy
- Core working hours
- Flexible schedule
Informal Culture
- Inclusive interview experience
Other Benefits
- Interview accommodations
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Wayve and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
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WAWayve
Machine Learning Engineer, App SW(m/w/x)
Leonberg
Full-timeWith Home OfficeSenior
AI/ML
Data Science
Nejo AI Summary
Developing end-to-end driving models and evaluation pipelines for autonomous driving AI at Embodied AI developer. Proven track record shipping production deep learning with Python/PyTorch expertise required. Direct influence on core AI architecture and training methodologies.
Requirements
- Proven track record shipping production deep learning
- Expertise in deep learning
- Proficiency in Python, C++, CUDA, and PyTorch
- Experience with real-time systems or robotics
- Ability to lead initiatives and mentor
- Prior work in autonomous driving
- Familiarity with human behavior modeling
- Experience integrating ML into production hardware
- Passion for self-driving cars
Tasks
- Develop robust end-to-end driving models
- Lead personalized and collaborative driving projects
- Build closed-loop and open-loop evaluation pipelines
- Curate real-world and synthetic data sets
- Influence architecture and training methodologies
- Collaborate cross-functionally to ensure integration velocity
- Mentor senior engineers on technical direction
Work Experience
- approx. 4 - 6 years
Education
- Bachelor's degreeOR
- Master's degree
Languages
- English – Business Fluent
Tools & Technologies
- Python
- C++
- CUDA
- PyTorch
Benefits
Flexible Working
- Hybrid working policy
- Core working hours
- Flexible schedule
Informal Culture
- Inclusive interview experience
Other Benefits
- Interview accommodations
Find the original job posting in its most current version here. Nejo automatically captured this job from the website of Wayve and processed the information on Nejo with the help of AI for you. Despite careful analysis, some information may be incomplete or inaccurate. Please always verify all details in the original posting! Content and copyrights of the original posting belong to the advertising company.
About the Company
Wayve
Industry
IT
Description
Wayve is the leading developer of Embodied AI technology, creating AI software and foundation models for autonomous driving systems.
Not a perfect match?
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