Root Access is looking for a Machine Learning Engineer Intern to help build the future of AI-assisted development tooling for embedded engineers, enabling them to program important machines across various industries.
Requirements
- Have hands-on experience training ML models (vision, NLP, or embedded/edge ML all welcome).
- Know your way around core ML concepts: model architectures, loss functions, optimization, evaluation metrics.
- Have experience with ML toolchains and workflows (e.g., PyTorch Lightning, Hugging Face, ONNX, TensorRT, Weights & Biases).
Responsibilities
- Train, evaluate, and debug machine learning models (e.g., deep learning, classical ML, multimodal models) using Python, PyTorch, and related frameworks.
- Use our internal AI-powered tooling to accelerate model development, dataset preparation, experiment tracking, and deployment workflows.
- Help test features like dataset validation, automated hyperparameter search, model introspection, and inference/runtime integrations.
- Provide structured feedback on usability, model behavior, edge cases, and failure modes (you’re part of the product loop).
- Build demo models, evaluation scripts, or experiment workflows that help us validate reliability and usability of the platform.
- Read academic papers, model cards, and technical documentation to cross-verify model performance and expected behavior.
Other
- This is a paid in-person spring internship that requires 16 hours/week commitment.
- Must be based in NYC or near.
- Have a Master’s in Mathematics, Data Science, or Engineering.
- Bring prior work or internship experience with model training, ML research, or applied AI engineering.
- Be hungry to contribute to an ambitious startup.
