Deep learning engineer - ai safety (f/m/div.)

Deep Learning Engineer – AI Safety (f/m/div.)

Your contribution to something big:

- Create, optimize and deploy new and innovative Deep Learning architectures based on RGB, LiDAR, Radar (2D and 3D point cloud), and fusion systems.

- Define and develop innovative safety of AI methods and measures, applicable to sensor fusion architectures for Perception in autonomous driving.

- Enthusiastic about AI reliability and/or long-tail learning approaches: Uncertainty Quantification, Model Calibration, Open Set Recognition, Open Set Object Detection, Anomaly/Novelty Detection.

- Join the Research and Innovation team to improve and optimize new solutions.

- Interact with other teams to ensure a connected and sound architectural solution.

- Interact with stakeholders to ensure technical understanding and alignment.

What distinguishes you:

- MSc or Ph.D. in Computer Science, Machine Learning, Mathematics or related AI field.

- At least 3-5 years of relevant experience in developing, training and evaluating AI methods.

- Strong programming skills in Python.

- Strong background in Digital Signal Processing, Computer Vision, Deep Learning.

- Strong mathematical background (in particular statistics).

- Experience with perception focused tasks, such as 3D Object Detection, Semantic Segmentation and Freespace Detection.

- Familiarity with transformer-based architectures related to perception methods.

- Experience with deep learning frameworks (e.g. TensorFlow/PyTorch).

- Solid technical mindset, teamwork and communication skills.

- Basic understanding of the interplay of hardware, software and algorithm architectures and applications.

Preferred Qualifications and Expertise:

- Familiarity with Anomaly Detection, Uncertainty Quantification, AI safety measures.

- Familiarity with knowledge distillation approaches and Foundation models.

- Familiarity with Ensemble based training methods.

- Experience with technical leading and mentoring others.

Cherry on top (plus):

- Experience with AI model deployment.

- Experience with OpenMMLab framework.

- Familiarity with tracking algorithms.

- Familiarity with ISOs 8800 (road safety), 26262 (Road vehicles – Functional safety) and 21448 (SOTIF).

Work conditions include:

- Flexible work conditions

- Hybrid work system

- Exchange with colleagues around the world

- Health insurance

- Medical office (psychology and general clinic) & Social Services Office on site

- Training opportunities (p.e., technical training, foreign languages training) & certifications

- Opportunities for career progression and continuous professional development

- Access to great discounts in partnerships and Bosch products

- Sports and health related activities

- Great access to public transports

- Free transport from Porto

- Flexible benefits platform

- Free parking lot

- Canteen

Make it happen! We are looking forward to your application!