Staff Machine Learning Engineer, Autobidder

4 weeks ago


Palo Alto, California, United States Tesla Full time
Job Summary

Tesla is seeking a highly skilled Staff Machine Learning Engineer to join our Autobidder team. As a key member of our team, you will develop forecasting algorithms for Autobidder, a state-of-the-art software product for monetizing front-of-the-meter and behind-the-meter energy storage systems.

Responsibilities
  • Lead the design, development, and evolution of our internal forecasting platform
  • Conduct creative research to identify new machine learning approaches that improve metrics and incorporate these into our platform
  • Identify and integrate new data sources to enhance model performance
  • Design scalable and reliable data pipelines to productionize and monitor both new and existing models
  • Become an expert in electricity price formation and market dynamics
  • Deliver various types of electricity market-related forecasts, including energy and ancillary service prices, load, regulation throughput, and reserve deployments for use in downstream algorithms
  • Mentor and develop a growing team of exceptional machine learning engineers into one of the leading electricity market forecasting teams
  • Collaborate with optimization engineers, traders, market analysts, and software engineers to ensure forecasts drive end-to-end value
Requirements
  • Proficiency in Python with at least 6 years of experience in software development, familiarity with software development practices, writing production-quality code, and agile development
  • Experience with a variety of forecasting algorithms and approaches, including statistical, regression, and deep learning algorithms
  • Experience with cloud-hosted systems and related tooling, including computing services AWS EC2, Google Compute Engine, container orchestration Kubernetes, Docker, and database and data warehouse platforms Amazon RDS, Google BigQuery
  • Expertise with relevant Python libraries, such as pandas, numpy, xgboost, lightgbm, pytorch, sklearn, plotly, seaborn, and streamlit
  • Demonstrated experience in developing and maintaining production ML platforms
  • Intrinsic motivation and passion for learning, collaboration, and working in the clean energy space
  • Degree in Mathematics, Machine Learning, Statistics, or equivalent experience
  • Domain expertise in forecasting, analysis, or trading in electricity markets ERCOT, CAISO, PJM, AEMO, and UK National Grid
  • Experience in shipping production models in time series forecasting or reinforcement learning
  • Familiarity with forecasting libraries, such as Nixtla, Pytorch-Forecasting, or Darts
What We Offer
  • Competitive pay and benefits package
  • Opportunity to work on cutting-edge projects in the clean energy space
  • Collaborative and dynamic work environment
  • Professional development opportunities


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