AI Application Intern - Unpaid

TiDB is an open-source, cloud-native, distributed SQL database for elastic scale and real-time analytics. Large and high-growth organizations in markets as varied as financial services, logistics, gaming, e-commerce and software as a service have successfully deployed and expanded their TiDB footprint on mission-critical applications. Our strong open-source community roots (34,000+ stars on GitHub), innovative products and inclusive culture are what draw passionate and dedicated people to our company. Learn more about PingCAP careers and join our team to be at the forefront of innovation and growth
As an AI Application Intern, you will work closely with our AI/engineering team to develop, test, and deploy AI-driven solutions. You’ll gain hands-on experience in building and optimizing AI models, integrating them into applications, and contributing to scalable solutions. This role is ideal for someone eager to bridge the gap between theoretical AI and real-world applications.
Responsibilities:- Assist in designing, training, and fine-tuning AI/ML models (e.g., NLP, computer vision, generative AI). - Collaborate with engineers to integrate AI models into applications/APIs. - Preprocess and analyze datasets for model training and validation. - Develop prototypes/POCs to demonstrate AI capabilities for business use cases. - Optimize AI models for performance, scalability, and accuracy. - Document workflows, experiments, and results for internal knowledge sharing. - Stay updated on emerging AI trends and tools.
Qualifications:- Currently pursuing or recently completed a degree in **Computer Science, AI, Data Science**, or a related field. - Familiarity with **Python** and AI/ML frameworks (e.g., TensorFlow, PyTorch, Hugging Face). - Basic understanding of **AI concepts** (e.g., deep learning, LLMs, prompt engineering). - Experience with data processing libraries (Pandas, NumPy) and REST APIs is a plus. - Strong problem-solving skills and curiosity about AI applications. - Ability to work independently and in a team.
Nice-to-Haves:- Portfolio/GitHub showcasing AI projects (e.g., chatbots, recommendation systems). - Knowledge of cloud platforms (AWS, GCP, Azure) or MLOps tools. - Exposure to Agile/Scrum methodologies.