(Senior) AI Engineer (m/f/d) - Verification & Validation

 

Join us as an AI Engineer (m/f/d) in our Verification & Validation team and help shape the future of autonomous mobility!

As the Verification & Validation team, we ensure that autonomous driving systems are safe, reliable, and ready for the road. We bridge simulation, testing, and real-world validation through AI-driven solutions and machine learning models. Our mission is to assess system performance, simulation fidelity, and data quality at scale.

We're a diverse group with backgrounds in machine learning, AI research, computer vision, and autonomous systems. We value innovation, collaboration, and the drive to push the boundaries of what's possible in autonomous vehicle validation.

What you will do

Be an AI engineer!

• Design, validate, and deploy AI-driven solutions for assessing autonomous driving systems, including scenario detection, anomaly detection, roadmanship scoring, and predictive analytics.

• Build scalable ML/AI solutions for simulation validation, perception analysis, behavior modeling, and scene understanding.

• Develop models for digital twin generation (vehicle models, 3D environments, sensor models) to support high-fidelity testing.

• Integrate ML models into cloud-based analytics pipelines (e.g., AWS SageMaker, Bedrock) for automated evaluation and monitoring.

• Work with multi-modal sensor data (camera, lidar, radar, GPS) to build robust models that generalize across diverse scenarios.

Be a researcher!

• Experiment with cutting-edge AI techniques (deep learning, transformer models, computer vision, GenAI) to solve novel validation challenges.

• Assess simulation fidelity and realism through AI-driven analysis of synthetic vs. real-world data.

• Develop metrics and methods to evaluate model performance, robustness, and scenario coverage.

• Contribute to internal research and share findings through documentation, presentations, and knowledge-sharing sessions.

Be a team player!

• Collaborate closely with V&V engineers, data scientists, and simulation teams to understand requirements and deliver AI solutions.

• Support cross-functional teams in integrating AI models into production systems and validation workflows.

• Mentor team members on ML best practices, model development, and deployment strategies.

• Contribute to continuous improvement of AI/ML infrastructure and methodologies.

 

What will help you to fulfill your role 

• You have a strong background in machine learning, AI, or computer science, with hands-on experience building and deploying ML models.

• You're proficient in Python and ML frameworks such as TensorFlow or PyTorch. Experience with deep learning, computer vision, and transformer models is highly valued.

• You have experience with MLOps practices—model training, deployment, monitoring, and CI/CD for ML systems. Familiarity with cloud platforms (AWS SageMaker, Bedrock, or similar) is a plus.

• You understand the full ML lifecycle from problem formulation and data preparation to model evaluation and deployment. You know how to build scalable, production-ready AI solutions.

• You have a collaborative and innovative mindset, comfortable working with stakeholders to translate business problems into ML solutions.

• You're curious and driven, excited about exploring new AI techniques and applying them to real-world challenges in autonomous driving.

Nice to have:

• Understanding of autonomous driving systems, V&V processes, or safety-critical AI applications.

• Experience with simulation platforms (Unity, Unreal, Carla, VTD) or digital twin development.

• Knowledge of safety standards (ISO 26262, ASPICE) or EU regulations for autonomous vehicles.

• Experience with feature engineering from multi-modal sensor data (camera, lidar, radar).

• Familiarity with GenAI, federated learning, or multi-agent systems.

• Background in computer vision, scene understanding, or perception systems.

• You're comfortable working in a multi-national team with occasional travel for meetings (e.g., PI Pl