Full Stack Engineer (Machine Learning Adjacent)

Community Energy Labs · Remote (USA)

Clean Energy
Posted 3 months ago

Machine Learning
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The Full Stack Engineering  role contributes to development of Community Energy Lab’s product stack by producing the smart controls needed to help our customers reach their goals, whether that’s saving money or saving the planet.


This role  will be responsible for understanding the data that needs to be collected; building and containerizing the recommended control algorithms to be used; and measuring the quality of the solution.  This role will also help to determine the ingress of data and the egress of control directives from these machine-learning based algorithms and other design activities that help to define how the software solution as whole is architected to produce the best results from our control algorithms.


Although we list specific technologies here and there, we’re most interested in hiring smart people who like solving problems, experimenting with different technologies and approaches to a problem and then converging on a solution and moving forward.  The ideal candidate will be comfortable building prototypes that help us learn what our Minimum Lovable Product is and the feasibility of various solutions before the final architecture comes into play.  Apply here.


Community Energy Labs enables buildings to use energy when clean sources of power are available and to use less energy overall by making smart decisions about when and how energy is used.  We primarily work with communities and schools, whose buildings make up nearly 30% of the commercial floor space in the US! 


Our software combines cutting edge control algorithms that use machine learning and thermal energy models along with traditional control techniques to make it happen.  And we combine that with an intuitive user interface that doesn’t require a PhD in mechanical engineering to make saving money and the planet easy for everyone - even cash-strapped schools with overworked building operators.


CEL's core AI-powered clean building control platform concept was a regional winner of CleanTech Open's 2020 international accelerator, an overall winner in the 2020 Madrona Venture Labs Go Vertical challenge, a 2021 impel+ building innovator, EPRI Incubate Energy 2021 cohort member and 2021 US Department of Energy SBIR awardee.  Follow CEL at Twitter and on LinkedIn.



  Stand-up meetings, sprint planning sessions, reflections, celebrations and other agile activities to help our team thrive.

  Building design specifications and technical specifications to provide feedback and insights for the system architects who will create the ML-adjacent software components.

  Constructing building models using industry standard tools, like Energy Plus and JModelica.

  Installing and comparing existing software solutions both locally and in the cloud to determine their technical readiness.

  Determining creative ways to train our algorithms quickly and without having to do expensive experiments in the field.

  Helping to design A/B testing frameworks to compare the performance of different algorithms, data inputs, and reward structures.

  Fixing bugs and issues found with live systems or in our pre-deployment testing.

  Documenting technical work so that others can understand.

Development work with tools such as PyTorch and TensorFlow.


// What will you need to be or become good at doing?


  Reviewing relevant literature regarding data collection, building modeling, and optimization techniques.

  Determining the right building attributes and equipment data to collect at the frequency needed to achieve results.

  Constructing building energy models using collected building attributes.

  Collecting and constructing data inputs from:  building attributes; streams like dynamic pricing and weather; and equipment and sensor data.

  Using publish/subscribe mechanisms to deliver data to and from our machine-learning based control algorithms to other areas of the system.

  Using and comparing the results from different types of optimization algorithms, from Model Predictive Control (MPC) to Reinforcement Learning (RL) to hybrid solutions.

  Help to design M&V techniques using various statistical methods to help understand the effectiveness of the solution as well as identify areas of improvement.

  Building tests to maintain a high-level of quality in the system.

  Integrating with databases of all types: relational, NoSQL, GraphDB, and TimeSeries.



  Containerizing solutions for easy deployment.

  Working in Linux-based operating systems without a windowing system. 

  Deploying solutions in our AWS-based cloud environment using EC2, Lambda, Amplify, S3, Cloudwatch, and others as needed.

  Familiarity with distributed systems architecture: datasets, parallel data processing, and distributed training.

  Understanding of storage, network, and compute resources and relationship to speed and cost tradeoffs.

  Commitment to stage-gate testing from data validation to model performance and code integration.

  Value and stay on top of security, privacy best practices 


// Did you know that more than 60% of startups fail due to conflict in early teams?  Early teams form the bedrock of work cultures.  Ideal CEL community members demonstrate:






  Entrepreneurial drive

  High accountability 

  Attention to detail balanced with... 

  A pragmatic approach to effort vs. value

  Empathy for customers & team


  Intrinsic drive to achieve results 

  Willingness to communicate & teach

  Willingness to listen & learn


  Solid work habits & organization


  Open-minded thought, speech & action

  Ability to self-soothe, repair conflict, tolerate discomfort


// This position initially has no supervisory responsibility over any employees working within the assigned product or program vertical.  As a startup employee a wide degree of agency, creativity and latitude is expected within the boundaries of the early stage objectives set by leadership. 


// This position is a full time position that may occasionally require extra hours and weekend work.  We will do what we can to meet caregivers half way and try to strategize and plan ahead so that we can minimize conflict between work, life and caregiving. Remote and part-time are absolutely on the table.



// Bachelor's degree in computer science, mathematics, or related field.  ML credential or commensurate work experience. 


// Did you know that more than 60% of startups fail due to conflict in early teams?  Early teams form the bedrock of work cultures.  Ideal CEL community members demonstrate:

  Passion for valuing and embracing diverse teams and thinking in tech and business.

  Experience working with emerging technology, innovation or new product development along the entire customer value chain in an enterprise environment.  

  Creatively identifying and developing strategies to overcome specific market barriers in the early stages of product life-cycles.

  Knowledge of energy efficiency, electric utility business and operations, and/or energy markets.

  Flexible and able to multitask; can work in an ambiguous, fast-moving environment while also driving toward clarity and solutions; demonstrated resourcefulness in setting priorities and executing.

  Possesses personal qualities of integrity, credibility, and commitment to the mission.

  A knack for balancing self-advocacy/development with a community orientation in work and life​.

  A commitment to technical excellence including understanding and articulating best practices.


// We’ve read the research and we know that certain underrepresented groups in tech might read our post and think “Oh, gee, well I only have nine out of ten qualifications.”  If our mission and this job speak to you and you have the interest and ability to work smart, learn, and grow with us then we want you to apply for this job.  Even if this is not the exact right opportunity for you, we want to know about you and keep you in mind for future posts.  


Community Energy Lab is an Equal Opportunity Employer.  All applications will receive consideration for employment without regard to legally protected characteristics.


// https://forms.monday.com/forms/55b77ca4e589f09712c4ae2e3278b2d8?r=use1

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