Member of Technical Staff - Data Engineer
About the role
Internet Backyard is building financial infrastructure for the compute economy. AI is making compute one of the most important resources in the world, but the systems around it are still early. We help data centers, neo clouds, and inference providers automate financial operations and create the trusted records needed for pricing, cash collection, market visibility, and future capital products. If you want to build systems that outlive you, help define a market, and shape compute into an asset class, join us. We're early, small, in person, well-funded, and moving fast.
What You’ll Do
- Work primarily on the pricing engine, tackling the data engineering challenges underneath it.
- Improve and extend the engine, build the modeling methodology, and wrestle messy, real-world data into something clean and usable.
- No product team to delegate to, no design reviews to schedule. Collaborate with Engineering, talk to customers to understand their pain points and spot opportunities, and move fast and own it fully.
What We’re Looking For
- You've built at an early-stage startup and loved it.
- You’re a generalist who’s happy wearing many hats and figuring things out without much hand-holding.
- You know the machine learning fundamentals cold. Linear regression, gradient boosting (XGBoost), and the broader ML toolkit.
- You can pick a modeling methodology and clearly justify why it's the right call.
- You've turned messy, real-world data into clean, usable pipelines. Wrangling dirty data is the core architectural challenge of our pricing engine.
- You're strong with Python and the quantitative research stack: numpy, pandas, polars, scikit-learn, backed by a solid mathematical foundation.
- You have a background in economics, econometrics, capital markets/quantitative trading, and you know how to reason about what actually drives prices.
- You understand why the financial infrastructure behind compute matters, and you want to be part of building it.
- Nice to have: Experience in energy markets, familiarity with our stack: SQLAlchemy, PostgreSQL, and RESTful APIs, and some TypeScript for when you touch the rest of the app.
How We Work
No layers, no handoffs, no hiding behind process. Everyone is close to the work and expected to use good judgment. Agency and autonomy are yours to lose. Be kind. We don't do jerks.
Compensation & Benefits
- Base Salary: $160,000-$200,000 USD
- Equity: 0.5%
- Location: SF Onsite, Open to discussion for exceptional remote candidates
- Healthcare, vision, dental, monthly stipend, private chef, 401(k), and whatever else you need to help build a generational company.