Machine Learning Engineer

About SafeAD

SafeAD is dedicated to developing the most advanced and reliable autonomous driving technology. Central to this mission is creating a core autonomy model adaptable across various platforms and use cases, trusted by major global automotive manufacturers and Tier 1 suppliers.

Key Responsibilities

• Develop and enhance large-scale machine learning models utilizing extensive in-house computational resources.
• Advance and implement new capabilities for SafeAD's multi-task scene understanding AI model.
• Optimize machine learning models for deployment on production-grade hardware.
• Improve and maintain the machine learning training pipeline for efficiency.
• Conduct real-world testing of software on autonomous vehicles.

Candidate Requirements

• Possession of a master's or doctoral degree in Computer Science, Robotics, or a comparable field or equivalent professional experience.
• Demonstated expertise in machine learning problem-solving, specifically using PyTorch.
• Proficiency in programming with C++ and Python languages.
• Strong team collaboration skills paired with an eagerness to learn and grow.

Specialization Areas

Applicants are invited to apply for one of the following focus areas, selecting the topic that aligns best with their interests and expertise:

• Map Topology & Geometry
• Sensor Fusion & Core AI
• Perception Tasks
• Planning & End-to-End Driving

What SafeAD Offers

• Opportunity to engage with cutting-edge autonomous driving technologies within a motivated team environment.
• A workplace culture featuring a flat organizational structure, rapid decision-making processes, and dedicated focus on technology.
• Flexible working hours to support work-life balance.
• Competitive compensation package including salary and stock options.

Additional Information

If you resonate with SafeAD's vision and wish to contribute to its mission, submissions of applications are welcomed with enthusiasm.