Moon
Software Engineering Intern, Data & Machine Learning
Glendale, CA · Intern · Internship
Sponsorship not specifiedDetected 16 days ago
PythonFastAPICode ReviewSQLAWSAzureRESTMachine LearningPyTorchscikit-learnPandasAirflowdbtData EngineeringData ScienceLLMsAI OrchestrationStatisticsMentoring
About the role
- Our data and ML layer powers core home services workflows- surfacing operational insights for service company owners and enabling predictive features that help users make better decisions.
- The data is real operational data at meaningful scale; the problems are genuinely interesting, and mistakes have real downstream consequences.
- This is not a data science internship where you run notebooks in isolation.
Responsibilities
- Applied ML & AI Integration Prototype and develop ML features in production or active development - applied to home services operational data. Integrate LLM capabilities into application features using LangChain, direct API calls, or agent orchestration patterns. Use AI tools actively across the whole workflow: EDA, code generation, debugging, documentation, and multi-step automated pipelines.
- meaningful data and ML work takes time to build, validate, and integrate into a production product.
Nice to have
- you've used LLMs to accelerate EDA, write boilerplate, or debug data issues, and you can describe exactly how.
- This is evaluated explicitly. Genuine intellectual curiosity about data - you want to know why a number looks wrong, not just make the error go away.
- Nice to Have ML library exposure: scikit-learn, PyTorch, or similar.
Skills
- EDA, code generation, debugging, documentation, and multi-step automated pipelines.
Company info
- AI-assisted development is your default mode, not an occasional tool. Document data models and transformation logic as part of the definition of done.
This listing is sourced directly from Moon's careers page and normalized into a canonical job model.