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Base is rebuilding America's power grid by deploying a distributed battery network that transforms today's centralized grid into a resilient, abundant system. As a Software Engineer on the Markets team, you will build and automate the decision infrastructure that governs how Base's battery fleet buys, sells, and dispatches power across energy markets.
You will own the full stack of market and control systems: designing and maintaining simulators, statistical models, algorithmic trading strategies, and automated decision-making infrastructure. Your work directly impacts Base's revenue and grid support delivery. Key responsibilities include:
- Design, build, and maintain infrastructure, platforms, and algorithmic components for battery control and financial market participation, including simulators and trading-strategy systems.
- Work closely with utilities, fleet, and market teams to enable participation in power markets under new modalities and across domestic and international geographies.
- Automate critical processes: backtest automation, regression-safe release processes for energy arbitrage policies, and iteration speed improvements.
- Build monitoring, alerting, and reporting systems that track performance of automated decision processes.
- Improve existing battery physical operation policies through data-driven optimization.
- De-risk, implement, and maintain ML-based methods (supervised learning, model-predictive control, policy imitation for dynamic systems) for automated decision-making.
Base's Markets team owns systems that decide how the battery fleet operates across every market. As the company expands into new markets and geographies, the challenges intensify: more uncertainty, more constraints, more capital at stake. You will help define, from scratch, how a distributed battery fleet should behave in power markets that were never designed for it.
Base is a venture-backed startup with a mission-driven culture. The company operates in-person and at high intensity. Priorities shift quickly, and your role may expand based on business needs.
REQUIREMENTS:
- Strong ability to systematize requirements, define success for ambiguous problems with multiple objectives, and propose pragmatic solutions.
- World-class ownership mindset: you own outcomes, not just tasks.
- Hands-on experience with AI/ML and HPC infrastructure from major cloud providers (AWS, GCP, Azure) or specialized platforms (Modal, Beam).
- Strong interest in applied math and machine learning methods.
- Experience solving MLOps or similarly challenging observability, monitoring, and versioning problems.
- Nice to have: experience with decision-making under uncertainty for stateful systems.
