We are looking for an AI/NLP expert with a passion for PyTorch and Transformer models. If you love complex challenges like text data classification and want to deploy your models into production, then read on!
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General Information:
- Start date: ASAP
- latest Start Date: 01/11/2025
- End date: 31/12/2025
- Extension: to be discussed, depending on new project pipeline
- Workload: 50-100%
- Home Office: possible
- Travel: No travel intended
- Working hours: Standard
Tasks & Responsibilities:
- Review and optimize a transformer architecture and training pipeline
- Implement and experiment with advanced techniques to improve performance on fields with severe class imbalance
- Conduct in-depth error analysis to identify patterns in misclassifications and propose data-driven improvements
- Refine and validate the data processing, label mapping, and stratified data splitting procedures to ensure maximum reliability
- Collaborate with our software architect to integrate the final, optimized model into a production-ready API for inference
- Document the final model architecture, training procedures, performance benchmarks, and best practices for future development
Must Haves:
- Educational background: advanced degree in AI/NLP or related field
- Min. 3 years hands-on experience fine-tuning Transformer models
- Demonstrable experience with multi-task and multi-label classification problems, expertise in handling severe class imbalance in text data
- Proficiency in deploying machine learning models as REST APIs
- Strong proficiency in PyTorch, including creating custom model architectures (e.g., multi-head classifiers) and custom loss functions
- Strong software engineering fundamentals and the ability to write clean, modular, and well-documented Python code, experience with Docker
- Professional proficiency in English
- Strong analytical and problem-solving skills, and collaboration abilities
We thank you for your application!
We are looking for an AI/NLP expert with a passion for PyTorch and Transformer models. If you love complex challenges like text data classification and want to deploy your models into production, then read on!
General Information:
- Start date: ASAP
- latest Start Date: 01/11/2025
- End date: 31/12/2025
- Extension: to be discussed, depending on new project pipeline
- Workload: 50-100%
- Home Office: possible
- Travel: No travel intended
- Working hours: Standard
Tasks & Responsibilities:
- Review and optimize a transformer architecture and training pipeline
- Implement and experiment with advanced techniques to improve performance on fields with severe class imbalance
- Conduct in-depth error analysis to identify patterns in misclassifications and propose data-driven improvements
- Refine and validate the data processing, label mapping, and stratified data splitting procedures to ensure maximum reliability
- Collaborate with our software architect to integrate the final, optimized model into a production-ready API for inference
- Document the final model architecture, training procedures, performance benchmarks, and best practices for future development
...Must Haves:
- Educational background: advanced degree in AI/NLP or related field
- Min. 3 years hands-on experience fine-tuning Transformer models
- Demonstrable experience with multi-task and multi-label classification problems, expertise in handling severe class imbalance in text data
- Proficiency in deploying machine learning models as REST APIs
- Strong proficiency in PyTorch, including creating custom model architectures (e.g., multi-head classifiers) and custom loss functions
- Strong software engineering fundamentals and the ability to write clean, modular, and well-documented Python code, experience with Docker
- Professional proficiency in English
- Strong analytical and problem-solving skills, and collaboration abilities
We thank you for your application!
