Intern, Machine Learning (Generative AI)

• Conduct exploratory data analysis (EDA) and feature engineering on images and associated text to optimize VLM performance for anomaly detection applications.
• Experiment with suitable VLM models and prompt engineering techniques for multi-modal anomaly detection on industrial datasets.
• Conduct research to explore new methodologies for leveraging VLMs in quality control/logistics.
• Document development processes, algorithms, and performance metrics for VLM-based anomaly detection systems, contributing to our knowledge base.

• Able to work full time for a period of at least 6 months.
• Undergraduate/Postgraduate currently pursuing a Degree/Masters in Computer Science, Computer Engineering, or a related technical discipline with an emphasis on machine and/or deep learning.
• Knowledge and experience dealing with computer vision, multimodal AI, and anomaly detection (e.g., image preprocessing, object detection, vision-language alignment, etc.).
• Experience with deep learning methods and frameworks: transformers, tensorflow/pytorch, scikit-learn, python, github.
• Curiosity-driven, independent thinking, and data-centric style of argument construction.
• Highly resourceful in gathering data from reliable and trustworthy sources, and the ability to summarize new knowledge fast.

• 🧠 Real-world experience apply classroom knowledge to practical, real-life work scenarios
• 📈 Skill-development build technical and soft skills while being part of the team “in-action”
• 💼 Opportunities to network and learn from industry professionals
• 🤝 Inclusive culture built on respect, collaboration, and empowerment

• Interview(s) with Hiring Manager, Business Leaders and HR

Bosch