Powerline

Powerline

Senior Optimization Software Engineer

Palo Alto · Senior

Sponsorship not specifiedDetected 474 days ago
PythonAlgorithmsGitSQLPostgreSQLMySQLCI/CDMachine LearningStatisticsForecastingElectrical EngineeringResearchCommunicationRenewable Energy

About the role

  • Join Powerline and help revolutionize the future of the electricity grid!
  • Our products help renewable project owners achieve strong economics and operational excellence, paving the way for a decarbonized and profitable future grid.
  • We work on exciting projects with leaders in the world's most lucrative and complex electricity markets.

Responsibilities

  • Develop optimization, forecasting, and control algorithms that automate battery and renewable projects to achieve maximum performance.
  • Lead as a market rules expert. Take responsibility for staying current on new developments in the wholesale markets Powerline operates.

Requirements

  • Strong knowledge of energy markets, EV/fleet optimization, batteries, virtual power plants, renewable energy, energy policies/regulations, and/or energy systems.
  • Proficiency in Python with professional software engineering standards.
  • Excellent communication skills and ability to articulate complex technical concepts.
  • Experience with Git, CI/CD pipelines, and agile development.
  • Experience with SQL-based databases (e.g., MySQL, PostgreSQL).
  • Experience with analytic dashboard development and visualization tools.

Company info

  • We are a disruptive, VC-backed cleantech company based in Silicon Valley.
  • Our cutting-edge technology leverages machine learning and artificial intelligence to optimize renewable energy and battery storage projects on the electricity grid.
  • This is an incredible opportunity to become an early and foundational team member at a climate tech company that is at a growth inflection point, addressing a critical problem in one of the most important and fastest-growing markets.

This listing is sourced directly from Powerline's careers page and normalized into a canonical job model.