Root Access · 1 day ago
Machine Learning Engineer -- Intern
New York, NY
Internship
Onsite
InternRoot Access is looking for a Machine Learning Engineer Intern to join their paid Summer 2026 internship cohort. The role involves contributing to ML projects, including dataset preparation, model experimentation, and exploring new frameworks or inference toolchains.
Information Technology & Services
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
Qualification
Required
Excited to help build AI-native developer tools
Contribute to ML projects across dataset preparation, model experimentation, benchmarking, and exploring new frameworks or inference toolchains
Train, evaluate, and debug machine learning models (e.g., deep learning, classical ML, multimodal models) using Python, PyTorch, and related frameworks
Use 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
Build demo models, evaluation scripts, or experiment workflows that help validate reliability and usability of the platform
Read academic papers, model cards, and technical documentation to cross-verify model performance and expected behavior
Hands-on experience training ML models (vision, NLP, or embedded/edge ML all welcome)
Know core ML concepts: model architectures, loss functions, optimization, evaluation metrics
Experience with ML toolchains and workflows (e.g., PyTorch Lightning, Hugging Face, ONNX, TensorRT, Weights & Biases)
Curious about how AI development tools could be radically better
Preferred
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, with opportunities to go full-time
Benefits
Paid
Company
Root Access
Helping teams configure and program mission-critical hardware with AI.
Founded in 2025
2-10 employees
Funding
Current Stage
Early StageCompany data provided by crunchbase