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Software Engineer, Algorithms & Infrastructure

Join Base Power as a Software Engineer to automate decision-making for a fleet of distributed batteries in power markets.

Location
Austin, TX, United States
Compensation
Not disclosed
Level
mid
Type
full time · On-site

Posted by employer 2 days ago

First seen on Joblaze 2 days ago

Last verified on the company career page 13 hours ago

Apply at Base Power Company → Save job Scanned from basepowercompany.com

What you'll build

  • Design, build, and maintain infrastructure for battery control
  • Automate backtest processes and release procedures
  • Build monitoring and reporting systems
  • Improve battery operation policies
  • Implement ML-based methods for decision making

Must have

  • Strong ability to systematize requirements
  • Hands-on experience with AI/ML and HPC infrastructure

Nice to have

  • Experience with decision-making under uncertainty

AI in the day-to-day

De-risk, implement, and maintain ML-based methods for automated decision making.

Not disclosed in this posting: compensation, years of experience, visa sponsorship.

Joblaze summary

In this role, the Software Engineer on the Markets team at Base Power Company focuses on developing and automating the decision-making infrastructure for the company's battery fleet, addressing complex market and control challenges. Key skills include experience with AI/ML, high-performance computing, and a strong grasp of applied mathematics. This position is suited for someone with a proactive mindset and a background in tackling ambiguous problems, particularly in dynamic environments. The team plays a crucial role in shaping how the battery fleet interacts with evolving power markets, directly influencing the company's financial outcomes.

Joblaze insights

  • Listed 2 days ago — first seen on Joblaze October 15, 2026. Last confirmed on Base Power Company's careers page October 17, 2026.
  • AI/ML appears in 53.6% of 468 comparable mid ai/ml roles in United States; HPC appears in 0.2% of 468 comparable mid ai/ml roles in United States.

Quick facts

Is the Software Engineer, Algorithms & Infrastructure role remote?
No — this is an on-site role in Austin, TX, United States.
Where is the role based?
Base Power Company is hiring for this position in Austin, TX, United States.
What's the tech stack?
Joblaze extracted these technologies from the posting: AI/ML, AWS, Azure, GCP, HPC.
What seniority level is this role?
Base Power Company targets mid-level candidates for this position.
Is this full-time or contract?
Full-time for this Software Engineer, Algorithms & Infrastructure role at Base Power Company.

From the original posting

About the Role

As a Software Engineer on the Markets team, you’ll build and automate the decisions our battery fleet and financial commitments run on, from real-time battery dispatch to long-term market participation. You’ll take ambiguous, high-stakes market and control problems and turn them into reliable, automated infrastructure: the simulators, models, and trading-strategy systems behind how our batteries buy, sell, and dispatch power.

This role has direct, measurable impact on Base’s top and bottom line. You’ll ship production decision infrastructure with backtest automation and regression-safe releases, deliver measurable improvements to our battery dispatch and control policies, and help bring ML-based methods like model-predictive control and imitation learning into production as we expand into new market modalities and geographies.

What You’ll Do

  • Design, build, and maintain the infrastructure, platforms, and algorithmic components we rely on for decisions about battery control and financial market participation — simulators, statistical models, algorithmic trading strategies.

  • Work closely with utilities, fleet, and market teams to enable our participation in power markets under new modalities and across additional geographies, domestic and international.

  • Automate the processes the Markets team relies on daily: backtest automation, release processes that prevent regressions in energy arbitrage policy behavior, and iteration speed improvements.

  • Build the monitoring, alerting, and reporting that tells us how our automated decision processes are performing.

  • Improve our existing battery physical operation policies.

  • De-risk, implement, and maintain ML-based methods (supervised learning, model-predictive control, imitation learning for dynamic systems like DAgger) for automated decision making.

 

What You'll Bring

  • Strong ability to systematize requirements, define success for ambiguous problems with multiple objectives, and propose pragmatic solutions.

  • A world-class ownership mindset — you own outcomes, not just tasks.

  • Hands-on experience with AI/ML and HPC infrastructure, from a major cloud provider (AWS, GCP, Azure) or specialized ones (Modal, Beam).

  • Strong interest in applied math and machine learning methods.

  • Experience solving MLOps or similarly challenging observability/monitoring/versioning problems.

  • Nice to have: experience with decision-making under uncertainty for stateful systems.

About the Team

Base’s Markets team owns the systems that decide how our fleet of batteries buys, sells, and dispatches power across every market we operate in. Every dollar of revenue and every megawatt of grid support we deliver runs through a decision this team automates — from real-time battery dispatch to long-term financial commitments. As we expand into new markets and geographies, the fundamentals get harder: more uncertainty, more constraints, more money on the line. This team gets to define, from scratch, how a distributed battery fleet should behave in power markets that were never built for it, with direct, measurable impact on Base’s top and bottom line.

Our Values

  • First Principles Thinking: Question assumptions. Principles > rules.

Standard company text repeated across Base Power Company's postings is omitted here.

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