About Centific
Centific is a frontier AI data foundry that curates diverse, high-quality data, using our purpose-built technology platforms to empower the Magnificent Seven and our enterprise clients with safe, scalable AI deployment. Our team includes more than 150 PhDs and data scientists, along with more than 4,000 AI practitioners and engineers. We harness the power of an integrated solution ecosystem—comprising industry-leading partnerships and 1.8 million vertical domain experts in more than 230 markets—to create contextual, multilingual, pre-trained datasets; fine-tuned, industry-specific LLMs; and RAG pipelines supported by vector databases. Our zero-distance innovation™ solutions for GenAI can reduce GenAI costs by up to 80% and bring solutions to market 50% faster.
Our mission is to bridge the gap between AI creators and industry leaders by bringing best practices in GenAI to unicorn innovators and enterprise customers. We aim to help these organizations unlock significant business value by deploying GenAI at scale, helping to ensure they stay at the forefront of technological advancement and maintain a competitive edge in their respective markets.
About Job
Help us fight email fraud with AI
Are you passionate about data and AI? Do you want to learn how to use data labelling to train AI models for email fraud prevention? If yes, then this internship is for you.
We are looking for a data analyst intern who will join our grading team and work on data labelling projects. You will be responsible for creating, reviewing, and validating data labels for various email fraud scenarios. You will also help us analyze the quality and performance of the data labels and the AI models.
This is an entry level position and an internship. You will work full-time, or part-time. You will receive training and mentorship from our experienced senior graders and managers. You will also have the opportunity to learn about email fraud prevention, AI, and data science best practices.
What you will do
- Create data labels for email fraud scenarios using a data labelling platform
- Analyze the quality and performance of the data labels and the AI models
- Provide feedback and suggestions for improving the data labelling process
- Collaborate with the data science team and other stakeholders on data labelling projects
- Learn and Grow: gain hands-on experience in the dynamic field of AI and data labeling, by working alongside industry experts and solving real-world problems
Payrate : $20/hr