Fermata Energy is pioneering vehicle-to-grid (V2G) systems. Our technology uses the battery capacity in parked electric vehicles (EVs) to provide services that make the electric grid run more efficiently and save customers money on their electric bills.

We’re at an inflection point in history with electric utilities using more green energy (wind and solar) and vehicle manufacturers projecting the rapid transition of all internal combustion vehicle sales to all-electric over the next decade. Utilities need grid-scale energy storage to smooth out intermittent generation and manage peak load. Parked EV batteries are the energy storage asset best positioned to provide the massive amount of energy storage required. Fermata is the company with V2G sites up and running now, saving customers money now and working to scale up deployments as fast as possible.

We are seeking an Optimization Engineer to help model, develop, and deploy the economic dispatch models responsible for efficiently and profitably managing bidirectional EV chargers and vehicles. These optimization models are utilized both externally, where they drive the dispatch of V2G and distributed energy resource systems in production, and internally, where they support our modeling R&D activities, market research simulations, and business development initiatives. This is a dynamic and cross-functional role that actively contributes to all these areas. One of the initial focal points will involve close collaboration with our Business Development and Data Science teams to model prospective customer sites and secure contracts, making this an exciting and impactful opportunity for the right candidate.

What you’ll do:

• Work closely with the optimization and machine learning teams to collaboratively develop and improve optimization models.
• Partner with internal business units to conduct in-depth financial analyses and simulations, aiding in data-driven decision-making and growing Fermata’s customer base
• Share and convey your analyses, technical concepts, and recommendations to stakeholders, ensuring that your insights are clearly understood and impactful in guiding the organization
• Contribute to Fermata's codebase by writing clean, well-tested code, reinforcing our commitment to maintain a high standard of coding practices.

Need to have skills:

• Bachelors or advanced degree in operations research, computer science or a related technical field.
• 2+ years of relevant experience or equivalent experience from pursuing an advanced degree
• Proven experience in formulating and solving optimization models, including Linear Programs (LPs) and Mixed-Integer Linear Programs (MILPs)
• Strong proficiency in Python and object-oriented programming
• Excellent written and verbal communication, including producing effective and compelling data visualizations
• Subject matter expertise in energy systems modeling and economic analysis
• A self-starter who is comfortable taking ownership in a fast-paced startup environment.

Nice to have skills:

• Experience with advanced optimization topics such as stochastic optimization, optimal control, decomposition methods, and meta-heuristics.
• Proficiency in machine learning, including forecasting and uncertainty quantification.
• Experience with a cloud platform, such as AWS, Azure, or GCP, is a plus.
  ### ** Although many of our opportunities are remote, candidates must be based in the U.S. and have the legal right to work in the U.S. in order to be considered.
  Fermata Energy is an Equal Opportunity Employer and complies with all applicable federal, state, and local fair employment practices laws. Fermata Energy strictly prohibits and does not tolerate discrimination against employees, applicants, or any other covered persons because of race, color, religion, creed, national origin or ancestry, ethnicity, sex (including pregnancy), gender (including gender nonconformity and status as a transgender individual), age, physical or mental disability, citizenship, past, current, or prospective service in the uniformed services, genetic information, or any other characteristic protected under applicable federal, state, or local law.