Sr. Machine Learning Engineer, Autobidder (Palo Alto)
Sr. Machine Learning Engineer, Autobidder
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The mission of the Autobidder team is to accelerate the world's transition to sustainable energy by building software products for monetizing energy storage and renewable assets. Our flagship product, Autobidder, automates wholesale electricity market participation for grid-connected batteries and renewable resources, maximizing revenues through optimal bidding across multiple revenue streams.
As a Senior Machine Learning Engineer, you will develop forecasting algorithms for Autobidder, research and prototype new market forecasts, and ensure these improvements translate into trading revenue gains. You will own production systems, ensuring their performance, reliability, and availability, contributing to the proliferation of battery storage and renewable projects globally.
What You'll Do
- Develop and deploy electricity market-related forecasts (energy prices, ancillary services, load, regulation throughput, reserve deployments, etc.)
- Research and incorporate new machine learning approaches to improve forecasting metrics
- Identify and integrate new data sources to enhance model performance and ensure scalable data pipelines
- Design and develop internal forecasting platforms supporting ML lifecycle and model hosting
- Become an expert in electricity price formation and market dynamics
- Collaborate with engineers, traders, analysts to maximize forecast-driven value
What You'll Bring
- Proficiency in Python with 4+ years of software development experience, including production-quality code and agile practices
- Experience with forecasting algorithms (statistical, regression, deep learning) and selecting appropriate models
- Experience deploying and maintaining ML models for time series forecasting in production
- Knowledge of cloud systems, compute services, containers, and data platforms
- Expertise in Python libraries like pandas, numpy, xgboost, pytorch, sklearn, etc.
- Passion for learning, collaboration, and clean energy
- Prefer academic background in machine learning, statistics, or related fields
- Optional: domain expertise in electricity markets (ISO, RTOs), power flow models, or forecasting libraries
Benefits
Competitive pay, benefits from day 1 including health plans, family benefits, 401(k), stock options, insurance, paid time off, and more.
Expected compensation: $124,000 - $240,000 annually, plus stock and benefits.
Additional Details
- Seniority level: Mid-Senior level
- Employment type: Full-time
- Industry: Automotive, Renewable Energy, Utilities
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