Job Title: Staff / Sr Staff Software Engineer

Company Name: Equilibrium Energy

Job Url: https://job-boards.greenhouse.io/equilibriumenergy/jobs/4002536005?utm_source=Otta

Job Description: What we are looking for
Our power sector is in the middle of a major transformation. Its increasingly renewable resource mix and demand-side changes require algorithmic management far beyond what was historically required. Because of this, scalable model development and deployment is at the heart of what EQ does. We are looking for Staff / Sr Staff Software Engineers who are passionate about helping to deliver this scientific platform – to stay at the forefront of AI/ML technology and operationalize those solutions at enterprise scale.

What you will do
You will be a member of EQ’s Science Platform team. Our Science Platform enables our internal data scientists, as well as external customers, to develop, experiment with, deploy, and monitor forecasting and optimization models at scale. We sit between our data and infra engineers and our scientists - developing frameworks for model development that are both robust and efficient to iterate within. We help bring the algorithmic capabilities of our scientists to a broad range of customer energy applications.

Key Responsibilities:

Abstract away the complexities behind the deployment and orchestration of a large number of forecasting workflows, enabling a fast model development lifecycle for our Science team
Integrate with data and compute infrastructure to optimize resource utilization and performance
Implement automated testing and monitoring for ML models in production
Maintain and iterate on our model registry and experiment tracking
Co-design frameworks that support model experimentation, hyperparameter tuning, training, and deployment
Partner with our Data Services team to incrementally improve our feature store and tie it to the EQ ontology
Collaborate closely with data scientists to understand new model requirements and together implement solutions that are robust, validated, and scalable
Collaborate with the Science Platform Simulation team to incorporate forecasting into physical and portfolio asset optimizations
Partner with our Product and Customer Delivery teams to enable external customers to perform similar tasks to our internal scientists, with minimal code divergence and following security best practices
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