Intern, Generative AI for Predictive Analytics

• Dive into Data: Conduct exploratory data analysis (EDA) and feature engineering on user text inputs to optimize AI model performance.
• Experiment and Innovate: Identify and experiment with suitable generative models and prompt engineering techniques for text-based predictive modeling on user input data.
• Conduct research: Explore new methodologies for leveraging GenAI in predictive analytics, validate models, and analyze experimental results to improve text-to-prediction pipeline performance.
• Document Your Journey: Meticulously document development processes, algorithms, and performance metrics for GenAI-based predictive 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 time-series, natural language processing, text analytics, and user input data (e.g., text preprocessing, sentiment analysis, named entity recognition, etc.).
• Experience with deep learning methods, frameworks and visualization tools: generative adversarial networks, transformer models, tensorflow/pytorch, scikit-learn, dash, 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