Senior AI Engineer

European Tech Recruit; München; Vor Ort; EUR 110.000 - 170.000; Vollzeit

Zusammenfassung

European Tech Recruit is helping a leading global technology organisation recruit a Senior or Principal AI Engineer specialising in end-to-end autonomous driving models in Munich, Germany. The role focuses on developing single neural network driving models that map sensor inputs directly to driving decisions, replacing modular pipelines.

You will design, develop and optimise end-to-end driving models, collaborate with top researchers and engineers, and advance safe, production-ready AI for

Qualifikationen

• MSc or PhD in Computer Science, Artificial Intelligence, Machine Learning, Robotics or similar.
• Commercial experience developing end-to-end driving models where a single neural network learns the driving task.
• Experience with modern end-to-end autonomous driving approaches such as behaviour cloning, driving policy learning, trajectory generation, planning networks, or Vision-Language-Action (VLA) models.

Aufgaben

• Develop and improve end-to-end autonomous driving models that directly generate driving decisions from multi-modal sensor inputs.
• Extend state-of-the-art driving architectures to improve robustness, safety, and generalisation across complex real-world scenarios.
• Design AI-based risk assessment and safety mechanisms for learned driving systems.
• Optimise models using large-scale real-world and simulation datasets.
• Evaluate model behaviour across nominal driving conditions and long-tail safety-critical edge cases.
• Collaborate with research and engineering teams to deploy production-ready AI systems.
• Stay up to date with the latest advances in end-to-end driving, foundation models, Vision-Language-Action (VLA), and autonomous driving AI.

Kenntnisse

End-to-end driving

Python/C++

Deep learning

Transformers

Communication

English

Travel (25%)

Ausbildung

MSc or PhD in CS/AI/ML/Robotics

Tools

Python

C++

Jobbeschreibung

Senior / Principal AI Engineer - End-to-End Driving Models

We are partnering with a leading global technology organisation developing next-generation AI-driven autonomous driving systems to recruit a Senior or Principal AI Engineer specialising in end-to-end autonomous driving models.

Unlike traditional modular autonomous driving stacks, this team is developing single neural network driving models that learn the complete driving task, from sensor inputs through to driving decisions. The focus is on advancing safe, robust, production-ready AI capable of operating in complex real-world environments.

This is a highly engineering-driven role where cutting-edge AI research is translated into production autonomous driving systems.

Role Overview

You will design, develop and optimise end-to-end driving models that directly learn autonomous driving behaviour from sensor data, replacing traditional perception to prediction to planning pipelines.

Working alongside world-class AI researchers and engineers, you'll develop next-generation driving architectures, improve robustness in safety-critical scenarios, and help solve some of the hardest challenges in autonomous driving through modern deep learning approaches.

Key Responsibilities

• Develop and improve end-to-end autonomous driving models that directly generate driving decisions from multi-modal sensor inputs.
• Extend state-of-the-art driving architectures to improve robustness, safety, and generalisation across complex real-world scenarios.
• Design AI-based risk assessment and safety mechanisms for learned driving systems.
• Optimise models using large-scale real-world and simulation datasets.
• Evaluate model behaviour across nominal driving conditions and long-tail safety-critical edge cases.
• Collaborate with research and engineering teams to deploy production-ready AI systems.
• Stay up to date with the latest advances in end-to-end driving, foundation models, Vision-Language-Action (VLA), and autonomous driving AI.

Required Experience & Skills

• MSc or PhD in Computer Science, Artificial Intelligence, Machine Learning, Robotics, Electrical Engineering or similar.
• Commercial experience developing end-to-end driving models, where a single neural network learns the driving task (for example mapping camera, LiDAR or BEV inputs directly to trajectory, planning or vehicle control outputs).
• Experience with modern end-to-end autonomous driving approaches such as behaviour cloning, driving policy learning, trajectory generation, planning networks, or Vision-Language-Action (VLA) models.
• Strong understanding of deep learning architectures including Transformers and multimodal neural networks.
• Experience developing AI for safety-critical autonomous driving applications.
• Hands-on Python and/or C++ development.
• Strong understanding of model evaluation, robustness testing, edge-case analysis, and deployment constraints.
• Excellent communication skills and collaborative mindset.
• Professional English required; German and/or Chinese are advantageous.
• Willingness to travel internationally (up to 25%).

Why Apply?

• Work on some of the world's most advanced autonomous driving AI.
• Develop next-generation end-to-end driving models rather than traditional modular ADAS pipelines.
• Solve challenging problems around safety, robustness, and large-scale deployment.
• Collaborate with leading AI researchers and engineers in autonomous driving.
• Take ownership of technology that will directly influence future production autonomous driving systems.

Recruiter's Note

This role is specifically looking for engineers who have built or significantly contributed to end-to-end autonomous driving models.

Experience with perception, SLAM, calibration, object detection, tracking, sensor fusion, or individual ADAS components alone is unlikely to be sufficient unless it formed part of developing a learned end-to-end driving model.

The strongest candidates will have hands-on experience designing, training, evaluating, or deploying AI models where a single neural network learns the driving task, producing outputs such as trajectories, planning decisions, or vehicle control directly from sensor inputs.

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