Engineer
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Our Company At Teradata, we believe that people thrive when empowered with better information. That’s why we built the most complete cloud analytics and data platform for AI. By delivering harmonized data, trusted AI, and faster innovation, we uplift and empower our customers—and our customers’ customers—to make better, more confident decisions. The world’s top companies across every major industry trust Teradata to improve business performance, enrich customer experiences, and fully integrate data across the enterprise. Our Internship Program Our Internship Program Our summer internship program lasts 10-12 weeks beginning in May/June and ending in August/September. We offer a fast-paced, flexible, fun environment where you will have the opportunity to work on meaningful projects and face new challenges every day. What You'll Do You will work on Projects Including: As an Agentic AI Engineer intern at Teradata, you’ll build cutting-edge intelligent agents that transform how users explore data, derive insights, and automate workflows across industries such as healthcare, finance, and telecommunications. You Will- Design and write high-performing and scalable software for training models.
- Craft and implement techniques to improve the performance and results of our training cycles, both on the SFT and the RL.
- Supporting agent management, evaluating open-source frameworks, and implementing logical data models and memory support.
- Contributing to low-code/no-code agent construction and the integration of external data sources for complex use cases.
- Pursuing a Bachelor’s, Master’s, or PhD degree in Computer Science, Electrical Engineering, or a related field.
- Expert in ML and fine-tuning large language models.
- Proficiency in Python and related ML frameworks such as JAX, Pytorch, and XLA/MLIR.
- Familiar with state-of-the-art techniques for preparing AI training data.
- Experience with post-training the models to reach SOTA-level performance.
- Familiar with designing and implementing large-scale model training frameworks.
- Collaborating with pre-training, reasoning, data, multimodal, applied, and product efforts to push the frontiers of model capability.
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