The Senior Software Engineer will design infrastructure for production services, support ML workloads, and ensure reliable battery operations in real-time.
Gridmatic is a high-growth startup and a new kind of energy company, delivering affordable, clean power by optimizing renewable energy and grid-scale batteries. With offices in the Bay Area and Houston, we bring together Silicon Valley–style innovation with deep, hands-on expertise in real-world power markets and energy retail.
As solar and wind become the fastest-growing sources of electricity, variability from weather and grid conditions makes energy prices more volatile. Gridmatic tackles this challenge with industry-leading forecasting and optimization—and gives our team the opportunity to work on problems that truly matter. Forecasting and trading energy are the foundation of what we do. We ingest large-scale data—weather, prices, load, and grid conditions—to build probabilistic machine learning forecasts that drive real operational decisions. Our work directly determines when power is bought, stored, or deployed, turning uncertainty into value for customers and the grid.
Our impact is measurable. Gridmatic is the most profitable participant in ERCOT’s wholesale market and operates the top-performing battery asset in CAISO. Profitable without venture capital, we offer a collaborative, low-ego environment where rigorous thinking, autonomy, and continuous learning are core to how we work.
The Role
We're looking for a Senior Software Engineer to join our Platform team and build the foundational infrastructure that powers Gridmatic. Our platform challenges are shaped by the nature of energy markets: forecasts and trading decisions run on tight schedules, battery dispatch commands must execute reliably in real time, and ML models need to train and deploy continuously as new data arrives.
What You'll Do
- Design and build our compute platform, creating infrastructure that supports production services, batch jobs, and ML training workloads
- Work on real-time systems for operating battery assets, where reliability directly impacts both revenue and grid stability
- Establish patterns, tooling, and best practices that help teams across Gridmatic run services reliably
- Make architectural decisions that shape how we build software as we grow
What We're Looking For
- Significant experience building and operating production infrastructure on a public cloud platform (we run on GCP, but AWS or Azure experience translates well)
- Hands-on experience with Kubernetes (we run on GKE and it's foundational to our platform)
- Proficiency in Python
- Experience with infrastructure-as-code tools like Terraform
- Either already know Go or have experience with a similar systems language (C++, Java, Rust) and are excited to work in Python and Go day-to-day
- Systems thinking—understanding how components interact, where failures can cascade, and how to build for efficiency, scalability, and resilience
- Clear communication, whether writing a design doc, reviewing code, or explaining a complex system to someone new to it
- Opinions about how to build reliable infrastructure, informed by experience with what works and what doesn't at scale
Nice to Have
- Background in ML infrastructure or training pipelines
- Experience with workflow orchestration tools (Flyte, Temporal, Airflow, or similar)
- Familiarity with observability tooling (we use Grafana + Google Cloud Monitoring)
- Experience with real-time systems
- Strong Linux fundamentals
- Prior work in domains where latency and reliability have direct business consequences
Join our team and make a difference! Click below or email us at [email protected].
Top Skills
AWS
Azure
GCP
Go
Kubernetes
Python
Terraform
Gridmatic Cupertino, California, USA Office
20450 Stevens Creek Blvd, Suite 100, Cupertino, CA, United States, 95014
Similar Jobs
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
The Senior Software Engineer will scale and optimize the Generative AI product infrastructure, improve performance, collaborate with teams, and implement best coding practices to enhance the conversation engine for enterprise solutions.
Top Skills:
Api DesignCloud InfrastructureGenerative AiMachine LearningMsteamsProgramming LanguagesSlack
Automotive • Big Data • Information Technology • Robotics • Software • Transportation • Manufacturing
As a Senior Software Engineer, you will design and build GM's Notification Platform, mentor junior engineers, and collaborate across teams to ensure system resilience and operational excellence.
Top Skills:
AWSAzureC++DockerGCPJavaKubernetesNoSQLPythonSQL
Artificial Intelligence • Cloud • HR Tech • Information Technology • Productivity • Software • Automation
As a Senior Software Engineer, you'll design and build core components of the Moveworks AI platform, collaborating with cross-functional teams to create scalable solutions and improve platform performance.
Top Skills:
Python,Golang,Java,C++
What you need to know about the San Francisco Tech Scene
San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.
Key Facts About San Francisco Tech
- Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Google, Apple, Salesforce, Meta
- Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
- Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
- Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
