Equilibrium Energy
Software Engineer - ML Platform (Staff / Sr Staff)
Equilibrium Energy, San Francisco, California, United States, 94199
Software Engineer - ML Platform (Staff / Sr Staff)
San Francisco or US Remote
About our Company Equilibrium Energy is revolutionizing the clean energy transition by developing innovative grid-scale energy storage solutions. Our technology and market platform helps utilities, independent power producers, and commercial customers optimize their renewable energy assets, improve grid reliability, and accelerate decarbonization. As a fast-growing climate tech company, we’re building infrastructure that will shape the future of energy markets and enable a sustainable energy economy.
Equilibrium Energy is a well-funded, Series B clean energy startup backed by some of the most prominent institutional investors in climate. New colleagues will share our vision that a next-generation energy company must be built from the ground up on deep industry expertise combined with an unwavering commitment to modern digital approaches. We’re looking for collaborative, talented, passionate and resourceful folks to join our team and help us lay the foundation for our important mission and ambitious plan.
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 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
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
Nice-to-have additional skills
An advanced degree in computer science or machine learning
Experience in time series forecasting
Experience building tools that support data scientists
Experience with Databricks and Spark or DagsterBackground in the energy and power systems sector
What we offer Equilibrium is composed of deeply knowledgeable industry experts across all our functions, with decades of experience in energy-specific commercial structuring, power systems engineering, machine learning, computational research, operations research, distributed and compute-intensive infrastructure, and modern software & ML engineering. Our experience in the space means we’ve previously built versions of nearly every technical component of our platform. We are now designing them better, and combining them in a holistic and novel way, to achieve global scale and climate impact. We pride ourselves on our deeply empathetic & collaborative culture, honest and direct but respectful communication, and our balanced, flexible, and remote-first work environment.
Employee benefits include:
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
Equilibrium Energy is a diverse and inclusive, equal opportunity employer that does not discriminate on the basis of race, gender, nationality, sexual orientation, veteran status, disability, age, or other legally protected status.
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About our Company Equilibrium Energy is revolutionizing the clean energy transition by developing innovative grid-scale energy storage solutions. Our technology and market platform helps utilities, independent power producers, and commercial customers optimize their renewable energy assets, improve grid reliability, and accelerate decarbonization. As a fast-growing climate tech company, we’re building infrastructure that will shape the future of energy markets and enable a sustainable energy economy.
Equilibrium Energy is a well-funded, Series B clean energy startup backed by some of the most prominent institutional investors in climate. New colleagues will share our vision that a next-generation energy company must be built from the ground up on deep industry expertise combined with an unwavering commitment to modern digital approaches. We’re looking for collaborative, talented, passionate and resourceful folks to join our team and help us lay the foundation for our important mission and ambitious plan.
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 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
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
Nice-to-have additional skills
An advanced degree in computer science or machine learning
Experience in time series forecasting
Experience building tools that support data scientists
Experience with Databricks and Spark or DagsterBackground in the energy and power systems sector
What we offer Equilibrium is composed of deeply knowledgeable industry experts across all our functions, with decades of experience in energy-specific commercial structuring, power systems engineering, machine learning, computational research, operations research, distributed and compute-intensive infrastructure, and modern software & ML engineering. Our experience in the space means we’ve previously built versions of nearly every technical component of our platform. We are now designing them better, and combining them in a holistic and novel way, to achieve global scale and climate impact. We pride ourselves on our deeply empathetic & collaborative culture, honest and direct but respectful communication, and our balanced, flexible, and remote-first work environment.
Employee benefits include:
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
Equilibrium Energy is a diverse and inclusive, equal opportunity employer that does not discriminate on the basis of race, gender, nationality, sexual orientation, veteran status, disability, age, or other legally protected status.
#J-18808-Ljbffr