Machine Learning Engineer

About SafeAD

SafeAD is dedicated to advancing intelligent and secure autonomous driving solutions, focusing on AI-driven, mapless technology. Our innovations are employed by leading automotive manufacturers and Tier 1 suppliers worldwide.

Role Overview

As a Machine Learning Engineer at SafeAD, you will engage with substantial machine learning models and extensive datasets using our expanding in-house computing infrastructure. Your responsibilities include enhancing and inventing new functionalities for our multi-task scene understanding AI model, optimizing and deploying these models on production hardware, streamlining the training processes, and conducting software validation within our autonomous vehicles.

Required Qualifications

Applicants should possess a Master's degree or PhD in Computer Science, Robotics, or have comparable experience. Proficiency in solving challenges through machine learning frameworks such as TensorFlow or PyTorch is essential, along with strong programming skills in C++ and Python. A collaborative mindset and eagerness to learn are crucial attributes for this role.

Specialization Areas

Candidates can select from four specialized areas aligned with their expertise and interests:

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

Benefits

• Opportunity to work on cutting-edge autonomous driving technologies within a motivated team
• Flat organizational structure enabling swift decision-making and a technology-centric environment
• Flexible work scheduling
• Competitive remuneration
• Eligibility for stock options

How to Apply

If you resonate with our mission and are ready to contribute to transformative autonomous driving technology, we encourage you to submit your application. We eagerly anticipate your response!