<div><b><span style="font-size:18px;">The Company</span></b></div><div>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. Gridmatic is a great place to work with a culture that values teamwork, continuous learning, diversity, and inclusion. We move quickly and fix things. We are environmentally and data-driven, with a growth-oriented, academic mindset. We value integrity as much as excellence.</div><div><br></div><div><b style="font-size:18px;">The Role</b></div><div>We are looking for an Atmospheric Engineer 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 engineering skills in a fast-moving, impactful startup environment. You will evaluate, and integrate complex atmospheric data and models into our prediction systems, which drive real-time energy trading and optimization decisions. You will join our ML team, owning the evaluation and ETL pipelines, while contributing to all design decisions..</div><div><br></div><div><b style="font-size:18px;">What you might work on:</b></div><div><b>Research and develop &amp; Internal Weather Models:</b></div><div>- Participating in the R &amp; D process of building our internal weather modeling capabilities.</div><div>- Post-processing existing SOTA AI forecasts to debias and recalibrate for our downstream power predictions.</div><div>- Evaluating model changes, pushing the boundaries of how we forecast weather variables relevant to the energy sector.</div><div><br></div><div><b>Evaluating &amp; Integrating External Weather Products:</b></div><div>- 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.</div><div>- Rigorously evaluating and monitoring the performance of integrated weather products, analyzing their impact across different regions, timeframes, and weather regimes. </div><div>- Working with external data providers (like NOAA) to define data requirements. Build, monitor, and maintain data ingestion pipelines.</div><div><br></div><div><b>Evaluating &amp; Running AI Weather Models In-house:</b></div><div>- Develop evolving metrics for AI weather models for our unique specifications.</div><div>- Optimize evaluation pipelines built with Cloud DataFlow</div><div>- Set up, run, and monitor SOTA AI weather forecasts on our GPU cluster.</div><div><br></div><div><b>Generic Time Series Modeling:</b></div><div>- 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.</div><div><br></div><div><b>Across all workstreams, you will be expected to:</b></div><div>- Write and maintain significant Python code within a Git-based software development workflow.</div><div>- Continuously learn about grid power modeling and the intricacies of energy markets.</div><br><br><h3>You might be a good fit if you:</h3><ul><li>Have a degree in Atmospheric Science, Meteorology, or related quantitative field.</li><li>Have experience working with atmospheric models (NWP and/or AI models) or large meteorological datasets.</li><li>Possess strong proficiency in Python programming.</li><li>Experience in Machine Learning.</li><li>Are comfortable working in a Linux environment and using Git for version control.</li><li>Have experience running computational jobs on clusters or cloud computing environments.</li><li>Have a demonstrated ability to analyze and interpret complex scientific data and model outputs.</li><li>Are an effective communicator, able to explain complex weather concepts to non-experts.</li><li>Are naturally curious and eager to learn about new domains, particularly energy systems and time-series modeling.</li><li>Thrive in a fast-paced, dynamic startup environment where priorities can evolve</li></ul><br><div><span style="font-size:17pt;">FAQ</span></div><div><br></div><div><b style="font-size:11pt;">What’s your policy on remote work?</b></div><div><span style="font-size:11pt;">We value the ability to work and collaborate in-person in our early stage as a startup, so Gridmatic has a hybrid policy of "50% in-office”. Most of the company works in our Cupertino office 2 or 3 days a week.</span></div><div><br></div><div>Join our team and make a difference! Click below or email us at careers@gridmatic.com. </div>

<p>Gridmatic Inc. is a high-growth ClimateTech startup based in the San Francisco Bay Area 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 6 years of profitable growth without raising venture capital. Gridmatic is a great place to work with a culture that values teamwork, continuous learning, diversity, and inclusion. We are environmentally and data-driven, with a growth-oriented mindset and we value integrity as much as excellence.</p>

Atmospheric Engineer

<div><b><span>The Company</span></b></div><div>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. Gridmatic is a great place to work with a culture that values teamwork, continuous learning, diversity, and inclusion. We move quickly and fix things. We are environmentally and data-driven, with a growth-oriented, academic mindset. We value integrity as much as excellence.</div><div><br></div><div><b>The Role</b></div><div>We are looking for an Atmospheric Engineer 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 engineering skills in a fast-moving, impactful startup environment. You will evaluate, and integrate complex atmospheric data and models into our prediction systems, which drive real-time energy trading and optimization decisions. You will join our ML team, owning the evaluation and ETL pipelines, while contributing to all design decisions..</div><div><br></div><div><b>What you might work on:</b></div><div><b>Research and develop &amp; Internal Weather Models:</b></div><div>- Participating in the R &amp; D process of building our internal weather modeling capabilities.</div><div>- Post-processing existing SOTA AI forecasts to debias and recalibrate for our downstream power predictions.</div><div>- Evaluating model changes, pushing the boundaries of how we forecast weather variables relevant to the energy sector.</div><div><br></div><div><b>Evaluating &amp; Integrating External Weather Products:</b></div><div>- 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.</div><div>- Rigorously evaluating and monitoring the performance of integrated weather products, analyzing their impact across different regions, timeframes, and weather regimes.&nbsp;</div><div>- Working with external data providers (like NOAA) to define data requirements. Build, monitor, and maintain data ingestion pipelines.</div><div><br></div><div><b>Evaluating &amp; Running AI Weather Models In-house:</b></div><div>- Develop evolving metrics for AI weather models for our unique specifications.</div><div>- Optimize evaluation pipelines built with Cloud DataFlow</div><div>- Set up, run, and monitor SOTA AI weather forecasts on our GPU cluster.</div><div><br></div><div><b>Generic Time Series Modeling:</b></div><div>- 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.</div><div><br></div><div><b>Across all workstreams, you will be expected to:</b></div><div>- Write and maintain significant Python code within a Git-based software development workflow.</div><div>- Continuously learn about grid power modeling and the intricacies of energy markets.</div><br><br><h3>You might be a good fit if you:</h3><ul><li>Have a degree in Atmospheric Science, Meteorology, or related quantitative field.</li><li>Have experience working with atmospheric models (NWP and/or AI models) or large meteorological datasets.</li><li>Possess strong proficiency in Python programming.</li><li>Experience in Machine Learning.</li><li>Are comfortable working in a Linux environment and using Git for version control.</li><li>Have experience running computational jobs on clusters or cloud computing environments.</li><li>Have a demonstrated ability to analyze and interpret complex scientific data and model outputs.</li><li>Are an effective communicator, able to explain complex weather concepts to non-experts.</li><li>Are naturally curious and eager to learn about new domains, particularly energy systems and time-series modeling.</li><li>Thrive in a fast-paced, dynamic startup environment where priorities can evolve</li></ul><br><div><span>FAQ</span></div><div><br></div><div><b>What’s your policy on remote work?</b></div><div><span>We value the ability to work and collaborate in-person in our early stage as a startup, so Gridmatic has a hybrid policy of "50% in-office”. Most of the company works in our Cupertino office 2 or 3 days a week.</span></div><div><br></div><div>Join our team and make a difference! Click below or email us at careers@gridmatic.com. </div>

Atmospheric Engineer

About the Job

About the Company

Gridmatic

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