Software Engineer, Modeling (Climate/Energy)

Oakland, California, United States | Full-time | Fully remote


In this role, you'll train, improve, analyze, and deploy ML models as part of our team working to estimate power plant emissions around the globe. This radical project is part of the Google AI Impact Challenge, a prestigious, action-oriented collaboration between Google AI,, WattTime, and other notable partners. The impact of this work has already caught the attention of Bloomberg, CleanTechnica, Grist and Vox.

It’s well known that fossil fuel emissions are the largest single driver of climate change, but less talked about are the millions of deaths each year from air pollution exposure. Although a few wealthy countries today currently track emissions with expensive continuous emissions monitoring systems, the vast majority of power plants worldwide are not continuously tracked, complicating environmental regulation and making advanced GHG control techniques impossible.

Our solution will combine different types of satellite imagery, as well as atmospheric chemistry datasets and real-time grid operations to complement and extend expensive, on-site power plant sensors with a global monitoring platform. With significant amounts of pollution going unreported, this work will combine a variety of different inputs, ML algorithms and AI techniques into a single project; satellite images will provide “eyes in the sky” to help ensure that power plant emissions have nowhere to hide.

The project is significantly underway: we have completed a proof of concept, established a working relationship with our incredible partners, and engaged in user outreach. Nonetheless, this role will require an entrepreneurial mindset in addition to world-class ML and AI expertise.  You will be joining the team as a senior developer who can both help manage the project timeline and requirements as well as be a technical contributor to our software that analyses and models large datasets.



Experience and skills can be gained in many different contexts. In one way or another, you have successfully navigated complex situations and developed and deployed the necessary tools  in your career that will help large energy users navigate innovative solutions to choose cleaner energy. 


  • Computer Science BS, or equivalent experience in a relevant field such as engineering, software development, physics, or data modeling.
  • 3+ years of full time development experience in a similar position
  • Practical experience using machine learning to model complicated systems
  • Experience working in a production software environment
  • Experience working with SQL databases and Python code
  • Prior experience giving day to day feedback with a development team to enhance the work and provide accountability.
  • Exceptional analytical skills: can think on your feet in high pressure situations
  • Exceptional listener and communicator: you ask questions, you seek out new information, you articulate complex points clearly and concisely
  • Resourcefulness: you’re equally comfortable coming up with ways to make it work as you are asking for what you need
  • Growth mindset: if you don’t know the answer now, you’re excited to learn
  • Impact driven: you do the boring work with as much attention and vigor as the fun stuff


  • Experience working with pandas, matplotlib or other graphing libraries like plotly.
  • Prior experience working with power grid, emissions and/ or energy data
  • Experience working on a project involving remote sensing 



  • Remote location in the U.S. Remote work location is required thru the pandemic. WattTime headquarters are in Oakland, CA. 
  • Authorized to work in the United States
  • Full time role with salary and benefits: $125,000 - $145,000
  • Application Deadline: February 11, 2021 
  • Send responses to the following: 
    1. What data science/engineering teams have you led before? How did you help different people on your team achieve success?
    2. What systems have you modeled before? If you haven’t modeled systems before, what are some of the problems you’ve solved in software?



We are practical, results-driven change makers. We believe nothing has more potential for fast, world-changing impact than software. We embrace change. We are lean and adaptable. We never confuse mere growth with real impact. We are all personally, fiercely committed to our mission. We are quietly radical in unexpected ways. We have allies, not competitors. We trust in data and everyone’s voice being heard. We know diversity is central to success. We consider respect non-negotiable: there are no jerks here. We offer competitive benefits and professional development opportunities.

Unlike most start-ups, our team is backed by a host of more than 200 volunteers who contributed to our founding and are happy to support us in terms of advice, networking and perspective. We also sit within the RMI family which brings additional upside in terms of robust benefits, support, industry connections and credibility.

WattTime is an Equal Opportunity Employer (EOE) and does not discriminate on the basis of race, age, gender, disability, or sexual orientation or classification.



WattTime is a nonprofit with a software tech startup DNA, dedicated to giving everyone everywhere the power to choose clean energy. We invented Automated Emissions Reduction (AER), which allows utilities, IoT device and energy storage companies, and any end user to effortlessly reduce emissions from energy, when and where they happen. Our cutting-edge insights and algorithms, coupled with machine learning, can shift the timing of flexible electricity use to sync with times of cleaner energy and avoid times of dirtier energy. We sell solutions that make it easy for anyone to achieve emissions reductions without compromising cost and user experience. WattTime was founded by PhD researchers from the University of California, Berkeley, and in 2017 became a subsidiary of Rocky Mountain Institute. WattTime is a founding member of Climate TRACE, a global coalition working together to monitor nearly all human-caused GHG emissions worldwide independently and in real time.