Construction is a $13 Trillion global industry and yet, it’s one of the least digitized. Our mission puts us at the forefront of a movement driven by former construction professionals looking to modernize how the world builds, fueled by rapidly increasing venture investment.
StructionSite is bringing the same computer vision and mapping technologies found in self-driving cars to the construction technology space. Our software allows project teams to communicate in the context of the jobsite anytime, from anywhere. As the only founding team in our space with actual construction experience, we understand our customers on a deep personal level. Builders want to build, not spend time tracking their work, so our software gives them superpowers to automatically capture and track their progress. The data we provide on the back end allows our customers to perform at a higher level and gives them a competitive edge to win their next project.
We’re a team of engineers, salespeople, product... managers, marketers, designers, operators, and evangelists. We value learning, humility, and ownership of our domains above all else and we’re looking for teammates who have the same appetite for growth, grit, and determination. If this sounds like you, we’d love for you to come build with us!
The Challenge:
We’re looking for a software engineer with experience solving high-value challenges using computer vision and machine learning in real world scenarios. Research potential solutions for technical feasibility, and collaborate with a fully remote/distributed product engineering team to deliver robust code into production that thousands of users around the world depend on to do their jobs.
- What You'll Do:
Transform Data Science prototypes to production-grade solutions at scale
- Architect and build a pipeline to intelligently extract 3D scene data from sequences of panoramic images, using a mix of geometric and deep learning approaches.
- You will be expected to lead from the front in following best practices in development and CI/CD methods.
- You will also be expected to be a strong independent contributor that is not afraid to implement/deploy the solutions.
- Design, code and deploy machine learning systems capable of processing large volumes of data
- Research and implement appropriate ML algorithms and tools
- Develop machine learning applications according to requirements
- Establish reusable data processing pipelines to enable rapid re-training and iteration through different ML methodologies
- Select appropriate datasets and data representation methods
- Design experiments and analysis methodologies that are statistically rigorous
- Run machine learning tests and experiments
- Perform statistical analysis and fine-tuning using test results
- Train and retrain systems when necessary
What You Have:
- Proven experience in Deep Learning and Computer Vision
- Master's Degree in Computer Science, Computer Engineering, Robotics, Computer Vision, Machine Learning or related field
- Practical knowledge of modern mapping/localization, detection, non-linear optimization, probabilistic filtering, and/or classification techniques
- Understanding of data structures, data modeling and software architecture
- Experience deploying ML and DL algorithms for regression and classification use-cases
- Deep knowledge of math, probability, statistics and algorithms
- Ability to write robust code in Python and C++
- Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (like scikit-learn)
- Experience setting up systems/frameworks (e.g., Docker and Kubernetes) within AWS or Google Cloud
