Internship -- AI/ML Engineer Intern
Role Overview
We’re looking for an AI/ML Engineer Intern to help our team develop proprietary finetuned models, create custom datasets, and improve our RAG system. We have an intense working environment meant only for the most ambitious engineers. If working hard and laughing along the way with awesome teammates is something you'd enjoy, then you'll fit right in!
What You’ll Do
Build, test, and debug AI-powered developer tools using Python, PyTorch, or similar frameworks.
Work with our internal LLM-based systems to generate code, configurations, and engineering insights.
Design experiments to evaluate model performance on tasks like code generation, toolchain integration, and semantic understanding of embedded systems.
Provide structured feedback on model accuracy, edge cases, and failure modes—you’re part of the research-product loop.
Help develop prompt strategies, fine-tuning datasets, and evaluation benchmarks.
Read research papers, vendor docs, and model logs to cross-verify outputs and improve system robustness.
You might be a good fit if you:
Have experience training or fine-tuning ML models, or working with open-source LLMs (e.g., LLaMA, Mistral, GPT-J).
Are comfortable using Python and ML libraries like PyTorch, Transformers, or scikit-learn.
Have worked on applied ML projects—NLP, code generation, recommendation systems, etc.
Are curious about how AI tools can improve engineering workflows—and want to shape that future.
(Bonus) Have built internal tools, worked with embedding models, or care deeply about model UX and interpretability.
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