Optimization Engineer

Number of employees

230

San Francisco, United States

Posted on: 2022-04-29

Category: energy

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Expired

Employment type:

Full time

Experience required:

Intermediate

Salary

Salary not provided

About the company:

At SPAN, we believe that powering homes with clean energy should be a simple and delightful experience that is technology-forward and human-centered. 

SPAN is advancing clean energy adoption with innovative hardware that replaces the electrical panel and becomes the home's center for connected power. It’s easier and faster to install, and it completely transforms the customer experience with intuitive energy controls and customizable backup power.

Our Mission  

SPAN develops products that accelerate the rapid adoption of renewable energy in the home. The flagship SPAN Smart Panel is the first true evolution for the traditional home electric panel, harnessing enhanced technology for metering, monitoring, and control. An expanded product suite of intelligent, integrated solutions radically lowers the cost and complexity of energy upgrades–including solar, batteries and EVs–empowering homeowners to be active, resilient and informed players in the energy market. 

The Role 

SPAN is developing advanced distributed grid infrastructure to reduce the cost and complexity of adopting electric appliances and distributed energy resources (DERs) and to enable better two-way control of energy flow within a home, of its associated DERs, and of the grid. The Span panel sits at the nexus of the grid connection, loads within a building, and DERs, enabling both grid-edge control and proactive home load management to improve grid reliability, resiliency, and security. As an Optimization Engineer, you will leverage your deep understanding of optimization, modeling, and control to support SPANS' effort to build out its energy management capabilities. You’ll be involved through the entire development process, from the acquisition of all additional third-party data, the initial design to remote monitoring in the field.

Responsibilities

Develop optimization and control algorithms from the ground up which includes:

  • Collaborate with product managers to understand requirements and market rules (e.g. electricity tariffs)

  • Translate requirements into energy scheduling and dispatch optimization models and define objectives for different use cases (e.g. peak shaving, cost minimization)

  • Develop real-time control algorithms either through the extraction of heuristic behavior or approaches such as model predictive control

  • Contribute to the development and maintenance of our simulation codebase for evaluating algorithm performance

  • Conduct batch simulation experiments to tune models and parameters for maximum performance

  • Collaborate with Data Scientists on requirements for inputs to the optimization (e.g. scenario selection, time series forecasting)

  • Integrate developed algorithms in our production code base with robust test coverage

  • Write Python code to manipulate and analyze timeseries data

  • Use fleet data to monitor algorithms in the field

About You 

Required Qualifications

We are seeking an Optimization Engineer who has:

  • Bachelor’s degree or higher in Mathematics, Engineering, or a closely related field

  • 2+ years of industry experience or PhD in developing optimization models for energy applications

  • Experience with optimization modeling packages such as PYOMO, CVXPY, or solver APIs (e.g. Gurobi, Cplex, Xpress)

  • Strong theoretical background in Linear Programming, Mixed Integer Programming, and Convex Optimization and solution algorithms

  • Experience developing physics models of electrical/mechanical systems

  • Software design experience and ability to write clean, maintainable, and shippable production code

  • Strong communication and interpersonal skills

  • Ability to understand and explain complex problems simply and effectively

Bonus Qualifications

We would love to hire someone who has:

  • Experience optimizing models for resource-constrained edge devices

  • Domain-specific knowledge either through previous work, courses in college, or side projects

  • Experience with Python libraries for numerical methods and timeseries data (NumPy, Pandas, SciPy)

  • Experience working with SQL and data visualization tools

Life at SPAN

SPAN embraces diversity and equal opportunity in a serious way. We are committed to building a team that represents a variety of backgrounds, perspectives, and skills. 

Headquartered in San Francisco’s vibrant SoMa neighborhood, we are an eclectic group of creative thinkers who value open communication, teamwork, and a ‘make it happen’ approach to addressing complex challenges. 

Our CEO, Arch Rao⁠—former head of the Tesla Powerwall team⁠—fosters an energetic and collaborative environment, with a strong emphasis on maintaining work-life-balance across the organization.

We’re hiring talented individuals who are driven by success and are passionate about shaping the future of renewable energy. If that sounds like you, we’d love for you to consider joining the rapidly growing team at SPAN.

The Perks:

⚡ Competitive compensation + equity grants at a well-funded, venture-backed company

⚡ Comprehensive benefits (including medical; dental, vision, life and disability insurance)

⚡ Comfortable, sunny office space located near BART and Caltrain public transit

⚡ Strong focus on teambuilding and company culture (events, meet-ups, clubs)

⚡ Flexible hours and unlimited PTO

Our Mission & Values:

At SPAN, we believe that powering your home with clean energy should be a simple and delightful experience that is at its essence human-centered and technology-forward.

Our core values include:

  • Making home energy more accessible, intuitive, and convenient.

  • Enabling homes and vehicles to be powered by the sun.

  • Building resilient homes with reliable power.

  • All-electric everything.

  • A more flexible & distributed grid.

Interested in joining our team? Submit an application today and we’ll be in touch with next steps!

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