Software Engineer, Power Markets & ML Infrastructure

Base Power; Austin (TX); On-site; USD 140,000 - 210,000; Full time

Job summary

Base, America’s next-generation power company, is seeking a Software Engineer for the Markets team in Austin to design and build automated decision infrastructure for battery dispatch and market participation. You will implement simulators, models, and trading strategies, shaping real-time and long-term operations of a distributed battery fleet.

You’ll collaborate with utilities, fleet, and market teams across geographies, deploying ML-based methods and backtest-backed releases while improving

Qualifications

• Experience with AI/ML and HPC infrastructure.
• Hands-on ML experience with major cloud providers (AWS, GCP, Azure).
• Experience solving MLOps or observability/versioning problems.

Responsibilities

• Design, build, and maintain the infrastructure, platforms, and algorithmic components for battery control and financial market participation — simulators, models, and trading‑strategy systems.
• Collaborate with utilities, fleet, and market teams to enable market participation domestically and internationally.
• Automate backtests and release processes to prevent regressions in energy arbitrage policy behavior; increase iteration speed.
• Build monitoring, alerting, and reporting to track performance of automated decision processes.
• Improve battery operational policies and de-risk ML-based methods (e.g., MPC, policy imitation) for dynamic systems.

Skills

AI/ML experience

HPC infrastructure

MLOps

ML methods

Cloud platforms (AWS/GCP/Azure)

Observability/versioning

Tools

Modal

Beam

AWS

GCP

Azure

Job description

Base, America’s next-generation power company, is seeking a Software Engineer for the Markets team in Austin to design and build automated decision infrastructure for battery dispatch and market participation. You will implement simulators, models, and trading strategies, shaping real-time and long-term operations of a distributed battery fleet.

You’ll collaborate with utilities, fleet, and market teams across geographies, deploying ML-based methods and backtest-backed releases while improving