What to Expect
The Opitcaster team develops and maintains the high-level control systems for Megapacks, Powerwalls, Virtual Power Plants, and microgrids. Our primary focus is on residential energy management solutions, which help homeowners minimize their electricity bills while providing exceptional customer experiences. By continuously forecasting solar production, energy demand, and more, our systems optimally dispatch energy in real-time. Additionally, we participate in electricity markets through the dispatch of utility-scale and aggregated batteries.
What You’ll Do
Contribute to the development and optimization of real-time energy management solutions
Develop production-level optimization algorithms
Enhance the accuracy of our battery forecasting models
Implement and evaluate algorithm performance through cloud-based tools that monitor our fleet
Develop and improve system control algorithms, including optimal control and model predictive control
Collaborate with team members to design and implement new customer-facing features
Apply machine learning techniques to improve system predictions and decision-making
What You’ll Bring
Currently pursuing an advanced degree in a relevant program such as Computer Science, Energy System Optimization, Operations Research, Data Science, or Power Systems Economics
Proficiency in several programming languages, with a preference for Python, and familiarity with Linux environments and version control systems like Git
Experience with big data systems (e.g., Spark, Airflow, AWS)
Experience in software development and shipping production code
Knowledge of optimization techniques (e.g., solvers, stochastic optimization) and machine learning models (especially time-series forecasting)
Strong problem-solving skills and effective communication abilities
Passion for sustainable energy and a commitment to advancing the field, with a bonus for any previous experience in the sector

Palo Alto, California

Intern/Apprentice