Lead software engineer, ML focus

2 weeks ago


Edinburgh, United Kingdom Building Atlas Full time

We are Building Atlas. Our vision is a fully sustainable commercial real estate sector. Our mission is to make this a reality through rapidly scaling building retrofits: the most sustainable building is the one that already exists. With a zero-touch approach, requiring nothing but the addresses of buildings, we help owners of commercial real estate portfolios: (1) find the best path to retrofitting their buildings; (2) avoid stranding risk and increase the value of their assets; (3) and get access to preferential financing and delivery partners to get the work done.

Our goal is to get as many buildings as possible retrofitted, so we recommend retrofit measures that bring the highest return on investment. Choosing the right building to focus on requires understanding its physics (building envelope and the energy systems), its current lease terms and use, its current value and future “green premium,” and the value of energy flexibility in a future grid. We gather all this data and build machine learning models to find the optimum retrofits across a portfolio of buildings.

To make this possible, we’re building a diverse team of people passionate about solving climate change in the built environment. We’re scattered around Europe and come from a variety of backgrounds, and we need your help

We’re looking for an experienced software engineering leader who has worked alongside ML and data scientists on a wide range of projects from conception to deployment. You’ll work side-by-side with data and research scientists to develop, train, and deploy models that drive our building retrofit recommendations. You will contribute to developing a SaaS platform that uses results of ML models to help our customers decarbonise portfolios of commercial buildings. Finally, you will lead all our software engineering efforts and assume management of other software engineers as the team grows.

Tasks
  1. Define the overall architecture for the SaaS platform and its underlying ML components
  2. Architect and implement data pipelines / ETL processes to support processing of data about buildings
  3. Collaborate with data scientists to take prototype models developed in notebooks and turn them into production-ready code, deployed in our SaaS platform
  4. Grow and manage a team of software engineers, focusing in equal parts on talent development and quality of product execution
Requirements

Minimum Qualifications:

  • Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field
  • 5+ years of professional experience as a full-stack software engineer or an ML engineer
  • 3+ years of experience with data engineering
  • 3+ years of experience training, testing, tuning, and deploying a variety of machine learning models in a production environment
  • Competency in Python, R or other modelling languages, and Jupyter notebooks
  • Expert familiarity with database technologies (e.g., PostgreSQL, MySQL) and cloud stacks, ideally GCP
  • Experience with and affinity for team leadership

Preferred qualifications:

  • Experience with a large variety of ML models and types of data, with a preference given to candidates who worked with geographic or urban datasets: addresses, building characteristics, energy, or GIS data
  • Experience with Google Cloud data processing and analysis tools - Dataflow, BigQuery, Colab, Vertex AI
  • Experience with enterprise SaaS development, ideally in a fast-paced startup environment
  • Experience with (or willingness to learn) Ruby on Rails
  • Passion for climate work




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