Senior Trading Engineer, Autobidder

1 Hour ago • 6-8 Years • Research & Development • Undisclosed

About the job

Job Description

Tesla's Autobidder team seeks a (Senior) Trading Engineer to optimize battery storage asset performance and revenue generation within the electricity markets. Responsibilities include developing Python-based analytical tools for performance monitoring and reporting, analyzing market designs and policy impacts, collaborating with machine learning and software teams, ensuring optimal market revenue, conducting batch experiments, and participating in on-call rotations. The role involves leveraging expertise in energy markets and software engineering to improve trading strategies and contribute to the advancement of renewable energy systems. The ideal candidate will possess strong analytical and communication skills, a collaborative mindset, and proficiency in Python or similar programming languages.
Must have:
  • Proficiency in Python
  • Understanding of European electricity markets
  • Analytical skills
  • Develop analytical & reporting tools
  • Collaborate with engineering teams
  • Ensure optimal market revenue
Good to have:
  • Experience in electricity market trading or research, particularly in energy storage
What to Expect

Are you passionate about revolutionizing energy systems? Join the Autobidder Operations team as a Trading Engineer and play a key role in advancing automated trading and asset optimization in the electricity markets. Autobidder manages the world’s largest fleet of battery storage assets, from utility-scale batteries to virtual power plants, driving innovation in renewable energy.

As a Trading Engineer, you’ll leverage your expertise in energy markets and software engineering to enhance reporting, performance attribution, and operational monitoring. Your solutions will enable proactive management of trading strategies and asset performance, directly influencing the success of energy assets and accelerating the transition to sustainable energy systems.

You’ll contribute to Tesla’s mission by optimizing battery revenues and advancing renewable power integration. With a passion for building and automating tools that deliver tangible results, a bias for action, and a collaborative mindset, you’ll thrive in our fast-paced team environment.
What You’ll Do
  • Develop Python-based analytical and reporting tools to monitor the performance of the wholesale battery fleet and generate actionable insights for future trading decisions
  • Analyze market design evolution and policy changes in key markets, providing insights into their impact on storage monetization, and engage with relevant stakeholders
  • Collaborate with machine learning, optimization, and software teams to deliver fundamental analysis and expertise that enhance our competitive edge in algorithmic electricity market trading
  • Ensure optimal market revenue generation for the markets under your responsibility through continuous monitoring and analysis
  • Conduct batch experiments using proprietary simulation tools, perform detailed forensic analysis of results, and identify opportunities for algorithmic improvements
  • Participate in on-call rotations to support Autobidder market operations
  • Lead discussions with internal teams, customers, and external organizations to communicate fleet performance and operational insights
What You’ll Bring
  • Bachelor’s degree in Science, Technology, Engineering, or Math or related field (or equivalent experience)
  • Proficiency in Python, or similar programming languages such as Java, Scala, C#, or C++
  • Understanding of European electricity markets (e.g., UK, France), including market design, trading strategies, and product structures
  • Analytical skills for extracting insights, making decisions in uncertain scenarios, and communicating technical results to diverse audiences
  • Collaborative mindset with a creative approach to problem-solving and a drive for team success


Preferred Skills:

  • Experience in electricity market trading or research, particularly in energy storage
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