Parisi Labs is an AI company building learning systems for complex physical environments. We combine historical and live data with real operational context to help people understand the present, evaluate possible futures, and make better decisions. Energy is our first proving ground. Ask The Grid is our public product for exploring the systems, markets, and assets that make up the power grid. We are a small technical team working across machine learning, data infrastructure, software, and real-world operations. About the Role: We are looking for an ML Data Platform Engineer to make the data behind our models and products dependable, understandable, and easy to use. This role sits at the intersection of data engineering and machine learning. You will transform messy, changing real-world sources into durable datasets and interfaces that researchers, product engineers, and customer-facing technical teams can trust. The goal is not to build a large platform for its own sake, but to accelerate bringing new models, product surfaces, and authorized data sources online without compromising correctness. What You Will Own: Build and improve ingestion, backfill, validation, and observability for high-volume, time-dependent data. Define clear data contracts and point-in-time semantics for model training, evaluation, and product use. Create reusable workflows for bringing new public and customer-authorized sources into the system. Build quality, lineage, freshness, and access controls that make data trustworthy in repeated use. Develop efficient datasets and query interfaces for ML and

Parisi Labs is an AI company building learning systems for complex physical environments. We combine historical and live data with real operational context to help people understand the present, evaluate possible futures, and make better decisions. Energy is our first proving ground. Ask The Grid is our public product for exploring the systems, markets, and assets that make up the power grid. We are a small technical team working across machine learning, data infrastructure, software, and real-world operations. About the Role: We are looking for an ML Data Platform Engineer to make the data behind our models and products dependable, understandable, and easy to use. This role sits at the intersection of data engineering and machine learning. You will transform messy, changing real-world sources into durable datasets and interfaces that researchers, product engineers, and customer-facing technical teams can trust. The goal is not to build a large platform for its own sake, but to accelerate bringing new models, product surfaces, and authorized data sources online without compromising correctness. What You Will Own: Build and improve ingestion, backfill, validation, and observability for high-volume, time-dependent data. Define clear data contracts and point-in-time semantics for model training, evaluation, and product use. Create reusable workflows for bringing new public and customer-authorized sources into the system. Build quality, lineage, freshness, and access controls that make data trustworthy in repeated use. Develop efficient datasets and query interfaces for ML and