We’re Hiring a Machine Learning Engineer!
- Wage based on experience $140,000 - $160,000
- Stock Options
- Benefits Package
- Remote from anywhere in Canada
Audette is creating carbon reduction plans for every existing building on the planet. We apply building science and machine learning to model the most important features that contribute to carbon emissions. Our platform turns data into retrofit strategies for commercial real estate’s zero-carbon future.
The world’s economies must transition to zero-carbon. With real estate representing 65% of global wealth and 40% of carbon emissions, there is no carbon-free future without carbon-free buildings. This is why we exist, and why we need you.
We are seeking a self-motivated Machine Learning Engineer to drive innovation for our industry-defining platform. You’ll play a vital role in accelerating machine learning models for identification of building features from aerial imagery, extrapolating gaps in core data, and predicting trends from disparate data sources.
This role reports to the Head of Technology and the scope includes:
- Collaborate with the Head of Technology and Building Science Lead to develop a cloud-native infrastructure for ML model development and deployment (MLOps), anticipate and lead the acquisition of appropriate technology and training datasets, advise on the curation and grooming needs for training data, and continuously adapt and refine models as business needs evolve.
- Work with stakeholders to define the business problems best suited for ML approaches, objectively measure value delivery, and collectively engage in feature extraction.
- Lead the adoption of and instruction for ML model training user interfaces.
- Work with engineers to integrate ML models with backend processes, data warehouses, analytics engine, and cloud infrastructure in support of a unified production environment.
- Contribute to team building and help recruit new technical talent as we grow.
Why this job is exciting:
We have a number of exciting and innovative projects in our pipeline including:
- A semi-supervised, multi-stage ML architecture that supports a feature pyramid network of CNN’s for object detection from satellite, aerial, and 3D geospatial data.
- A regression model that imputes both categorical and continuous variable data in core datasets.
- A regional forecasting model for the emissions, costs, and savings for going carbon-free.
- A deep learning model that correlates disparate data sets to enable planetary-scale carbon-reduction opportunities.
As Audette grows across portfolios and continents, the intelligence you create will be re-incorporated into our architecture, making each iteration faster and more accurate. This is how we achieve our vision of a carbon reduction plan for every building on the planet.
- Expertise with deep learning models and architectures in an enterprise environment, including convolutional neural networks, generative models, self-supervised learning, time-series methods and probabilistic models.
- Experience with the Python scientific computing stack and one or more deep learning frameworks such as PyTorch or Tensorflow.
- Curiosity and enthusiasm for independent research; the ability to learn and implement new modelling approaches from the ML literature; and the ability to validate and iterate modelling approaches to achieve target metrics and deliver on project scope.
- Experience with Google cloud, AutoML, and VertexAI is a plus.
Working at Audette:
Together, we’re creating something unprecedented to tackle a huge global problem. To make this happen, we strive to create a best-in-class workplace in many areas, including continuous skills improvement, servant leadership, empathic communication, high-trust culture, and more.
As a member of Audette you will work on challenging problems of critical importance with a team of building science and software engineers. You will have a major impact over our technology, product and company culture.
Audette is committed to creating an inclusive employee experience for all. Regardless of race, gender, religion, sexual orientation, age, disability, or parental responsibilities, we firmly believe that our work is at its best when everyone feels free to be their most authentic self.
Our Hiring Process:
- Initial screening interview (15 mins)
- Skills Test
- Second Technical interview (1-2 hours)
- Final interview (30 mins) with team
- Reference checks + offer