Machine Learning Engineer; Production AI

ZF LIFETEC is one of the world's leading suppliers of passive safety systems. As Simi Automotive, a global innovation leader for motion capture software and complete systems for recording and analyzing human movements and a subsidiary of ZF LIFETEC, we contribute our experience with camera-based systems to developing solutions for vehicle interior monitoring and occupant safety. We are working in collabration with ZF Lifetec teams to monitor the quality of production processes using AI.

We are looking for a motivated and skilled ML Engineer to join our AI team. In this role, you will contribute to a range of exciting projects in production quality monitoring and vehicle interior monitoring. Working closely with software developers and data engineers, you will help design, train, deploy, and evaluate state-of-the-art machine learning algorithms for our automotive demonstrators.

• Translate high-level requirements into a well-defined ML strategy

• Identify state-of-the-art machine learning and computer vision techniques suited to our use cases

• Design, implementation, and analysis of machine learning and computer vision applications, from proof-of-concept to production

• Train and evaluate deep neural networks for tasks such as image classification, object detection, segmentation, and pose estimation

• Develop well-structured, documented code for training pipelines, data pipelines, qualitative analysis, and performance evaluation

• Perform data sampling and analysis for specific ML tasks

• Analyze and document the quantitative and qualitative performance of ML models

• Provide feedback and recommendations on data collection and labeling

• Monitor and analyze model performance in production environments

• Master's degree in Computer Science or a related field (please include your diploma and transcript with your application)

• At least 3 years of professional experience in machine learning and computer vision, or a PhD in machine learning

• Hands-on experience training and evaluating models for tasks such as object detection, classification, keypoint detection, and segmentation

• Solid knowledge of current neural network architectures

• Experience using Microsoft Azure for ML workflows

• Strong programming skills in Python and relevant libraries such as PyTorch and OpenCV

• Experience implementing research papers, ideally showcased on a personal Git Hub profile

• Understanding of data distributions and their impact on model training

• Knowledge of and experience in applying modern software engineering best practices

• The opportunity to take on responsibility and make a real impact

• Flat hierarchies and flexible working hours

• A new, modern office in Unterschleißheim, with the option to work from home part of the time

• A highly motivated team of software developers and machine learning experts working together to make driving even safer

• Working in an agile (Scrum) setting on a variety of ML tasks with real impact on production efficiency.