Technical Intern (Masters or PhD)

Centific
United StatesPosted Aug 31, 2026

About the role

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 We are looking for entry level Data Scientists/Applied Scientists (through student worker program) with strong Python coding skills, passion for AI quality, the ability to learn, and hands-on experience in delivering exceptional AI experiences, which our customers have come to expect.

Responsibilities

Keeping a keen eye on the latest developments in the broad AI community. Working with science, engineering, and program management teams to integrate the latest large language models (LLMs) such as OpenAI models and open-source models into production systems. Collaborating with other researchers, data scientists, product managers, and engineers in the team to build tools and improve the end-to-end AI Quality of our production systems. Leveraging data from various sources and domains to design and implemen

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