What To Expect
The mission of the Autobidder team is to accelerate the world's transition to sustainable energy by maximizing the value of storage and renewable assets. We achieve this by building state-of-the-art software products for monetizing front-of-the-meter and behind-the-meter energy storage systems. Our flagship product, Autobidder, is an end-to-end automation suite for wholesale electricity market participation of grid connected batteries and renewable resources that maximizes revenues by optimally bidding in all available revenue streams in these markets. We are a multidisciplinary algorithmic trading team with expertise in machine learning, numerical optimization, software engineering, distributed systems, electricity markets and trading. We have a proven track record of operating storage assets and delivering high revenues in both utility-scale and Virtual Power Plant (VPP) settings. Our products currently manage over 7GWh of energy storage worldwide and we're slated for rapid growth on the horizon.
As a (Senior) Algorithms Engineer, you will be responsible for steering the evolution of Autobidder's bidding and automation algorithms. This includes rapid iterations when entering new markets and devising sophisticated algorithmic approaches to optimize revenues and increase automation in advanced markets. You will develop deep expertise in electricity markets and leverage your technical skills to craft algorithms that help Autobidder deliver best-in-class performance. You will be intimately familiar with the performance and operational nuances of assets operated by Autobidder and will serve as the feedback loop between operational learnings and algorithmic advancements to ensure our algorithms deliver real-world value. You will own production systems and be responsible for their performance, reliability, and availability. Your work will help proliferate battery storage and renewable projects around the globe.
What You'll Do
Algorithm Development: Design, implement, and maintain production code for sophisticated bidding, optimization, simulation, and forecasting algorithmsResearch and Innovation: Prototype, benchmark, deploy and monitor advanced algorithmic features that account for uncertainties in prices and clearing outcomes, optimally allocate quantities to maximize risk adjusted revenues, reason about interactions with strategic competitors, account for influence of quantity on clearing prices, etc. for large fleets of utility-scale storage assets and Virtual Power PlantsDomain Expertise: Become an expert in electricity markets and grid, and the various facets of operating in themTechnical Leadership: Guide algorithmic decisions to balance performance and complexity, and make thoughtful design and infrastructure choices that facilitate a positive developer experience in the long runTooling, Simulation and Monitoring: Develop tooling and simulation systems to monitor and track field performance of assets. Define metrics to quantify, track, and improve specific areas of performance, and drive algorithm changes to enhance asset performance under managementRoadmap Planning, Product and Business Development: Plan technical roadmaps and lead execution. Inform product definition and business developmentMentorship and cross-functional collaboration: Mentor and develop a growing team of exceptional algorithm engineers. Work with ML engineers, traders, market analysts, and software engineers to ensure algorithms drive end-to-end value
What You'll Bring
4+ years' experience in developing and maintaining production software systemsProficiency in modern programming languages, such as PythonExperience in writing high-quality production codeExperience in building real-world products and solutions using numerical optimization technology (LP, MILP, nonlinear optimization, etc.) and solvers such as Gurobi, XPRESS, GLPK, CPLEX, etc.Knowledge of the energy and electricity market
Preferred, additional skills:
Domain expertise in forecasting, analysis, or trading in the GB electricity market (or other electricity markets)Experience with cloud-hosted systems and related tooling, including compute services (e.g. EC2, GCP Compute Engine) and container orchestration (e.g. Kubernetes, Docker)Expertise in numerical optimization, operations research, and related mathematical fields, such as stochastic control, optimal control, and computational financeExperience in researching, developing, and deploying new algorithmic strategies to solve complex optimization problems, including decision-making under uncertainty, scenario optimization, MDPs, financial risk modeling, and distributed/decentralized control
, Tesla
