Notice (8): Trying to get property 'title' of non-object [ROOT/templates/Jobs/details.php, line 11]Code Context                <div class="row">
                    <div class="col-auto"><p><?php echo $job->jobcategory->title;?></p></div>
                    <div class="col-auto"><p><?php echo $job->jobtype->title;?></p></div>
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Cake\Controller\Controller::render() - CORE/src/Controller/Controller.php, line 699
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Cake\Http\Runner::handle() - CORE/src/Http/Runner.php, line 73
Cake\Routing\Middleware\AssetMiddleware::process() - CORE/src/Routing/Middleware/AssetMiddleware.php, line 68
Cake\Http\Runner::handle() - CORE/src/Http/Runner.php, line 73
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Cake\Http\Server::run() - CORE/src/Http/Server.php, line 90
CDI
Applied Time Series AI Engineer

BES (Business & Engineering Solutions) is growing and thus welcoming new Applied Time Series AI Engineer in our Automotive team.
Requested profile.

You will join our AI team and play a key role in applying state-of-the-art time series foundation models to real-world automotive and industrial challenges. In this role, you will bridge the gap between cutting-edge AI research and practical implementation, developing scalable, high-performance solutions that leverage sequential data to drive innovation and impact across the business.

Apply existing time series foundation models to real-world industrial datasets
Fine-tune and adapt models to specific use cases, ensuring high performance and reliability
Implement, optimize, and maintain scalable pipelines for model training, evaluation, and deployment
Collaborate with researchers and cross-functional teams to integrate AI solutions into production systems
Develop proofs of concept to validate model approaches and support decision-making
Ensure reproducibility, efficiency, and scalability of experiments in HPC or cloud environments
Keep up to date with the latest advancements in time series modeling and foundation model
Key skills

Python
Pytorch
Time-Series
Foundation Models
Machine Learning
Computer Vision
AI
Experience required

MSc or PhD in Computer Science, Data Science, Engineering, Physics, or Mathematics
2–5 years of professional experience in machine learning or applied AI
Strong programming skills in Python (C++ is a plus)
Hands-on experience with deep learning frameworks such as PyTorch or TensorFlow
Practical understanding of time series data, preprocessing, and feature engineering
Experience with data pipelines, HPC/cloud environments, and scalable workflows
Ability to work independently and collaboratively, manage multiple tasks, and meet deadlines
Eagerness to learn new AI technologies and apply them to industrial applications
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