The Company

Gridmatic Inc. is a high-growth startup with offices in the Bay Area and Houston that is accelerating the clean energy transition by applying our expertise in data, machine learning, and energy to power markets. We are the rare startup that has multiple years of profitability without raising venture capital. At Gridmatic, we foster a collaborative and inclusive culture where learning and growth are constant. We move quickly, solve problems with integrity, and balance environmental responsibility with data-driven excellence.

The Role

We are looking for an Atmospheric Scientist to apply their deep expertise to directly influence our models and strategies, contributing to the clean energy transition. This is a hands-on, individual contributor role where you will leverage your scientific knowledge and technical skills in a fast-moving, impactful startup environment. You will explore, evaluate, and integrate complex atmospheric data and models into our prediction systems, which drive real-time energy trading and optimization decisions. You will collaborate closely with our ML, engineering, and data science teams, teaching others about weather phenomena while learning about grid power dynamics and time-series modeling techniques.

What you might work on:

Research and develop & Internal Weather Models:

-Engaging in more open-ended research and development to build or refine our own weather modeling capabilities.

-Fine-tuning existing state-of-the-art AI models (e.g., based on AIFS, NeuralGCM).

-Post-processing existing SOTA AI forecasts to debias and recalibrate for our downstream power predictions.

-Incorporating and evaluating model changes, pushing the boundaries of how we forecast weather variables relevant to the energy sector.

-Educate and inform the broader team about atmospheric phenomena and weather forecasting concepts.

-Potential to publish research and findings derived from your work, contributing to the scientific understanding at the intersection of atmospheric science and energy, where appropriate and aligned with business goals.

Evaluating & Integrating External Weather Products:

-Surveying and evaluating the suitability of various Numerical Weather Prediction (NWP) and commercially available AI weather forecast products for our power production and price models.

-Rigorously evaluating and monitoring the performance of integrated weather products, analyzing their impact across different regions, timeframes, and weather regimes.

-Working with external data providers (like NOAA) and internal engineers to define data requirements. Work with engineers to build, monitor, and maintain data ingestion pipelines.

Evaluating & Running AI Weather Models In-house:

- Develop evolving metrics for AI weather models for our unique specifications.

- Set up, run, and monitor SOTA AI weather forecasts on our GPU cluster.

Generic Time Series Modeling:

-You might also apply your modeling skills to improve generic time series models for power production or energy price forecasting, using ML libraries like PyTorch or JAX.

Across all workstreams, you will be expected to:

-Write and maintain significant Python code within a Git-based software development workflow.

-Continuously learn about grid power modeling and the intricacies of energy markets.