Software Engineer - ML Platform (Staff / Sr Staff)

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
• Stay up-to-date with the latest advancements in ML engineering and integrate best practices into the platform

This role contributes to building an AI operating system for the power sector that enables a cleaner, more resilient energy future by operationalizing machine learning solutions at enterprise scale to manage renewable energy resources and demand-side changes algorithmically.

The minimum qualifications you'll need:

• A commitment to clean energy and combating climate change
• Proficiency and 5+ years experience in Python software development
• Familiarity with automated build, deployment, and orchestration tools such as CI/CD, Pants, Docker, Metaflow, Argo, and Kubernetes
• Strong understanding of data pipelines, ETL, and data infrastructure
• Experience with observability tooling like Grafana, Honeycomb, and Prometheus
• Experience with common machine learning algorithms and libraries (xgboost, sklearn, pytorch, pandas, polars, pandera)
• Prior experience in operationalizing machine learning workflows
• Agility in working with cross-functional teams and adapting to new work methodologies
• Familiarity with agile practices, or a willingness to learn
• Strong communication skills for collaborating within a remote-first team that works internationally across timezones

What we offer:

• Competitive base salary and a comprehensive medical, dental, vision, and 401k package
• Opportunity to own a significant piece of the company via a meaningful equity grant
• Unlimited vacation and flexible work schedule
• Accelerated professional growth and development opportunities through direct collaboration and mentorship from leading industry expert colleagues across energy and tech
• Deeply empathetic & collaborative culture, honest and direct but respectful communication, and balanced, flexible, and remote-first work environment

Equilibrium Energy is a team of technologists, power market experts, and AI pioneers reimagining how the world's most critical industry operates, building a first-of-its-kind AI operating system for the power sector to enable a cleaner, more resilient energy future.