Treeswift empowers energy companies to modernize their field work to meet unprecedented growth and challenges ahead due to rising threats like severe storms and wildfires, increasing pressure on affordability and unprecedented demands for system expansion.
Requirements
- Proven track record of training and deploying machine learning models at scale for commercial use cases.
- Experience in segmentation and object detection of point cloud data or image data or other sensor data.
- Experience creating, curating, and cleaning training datasets
- Strong programming skills in Python
- Expertise in deep learning libraries such as PyTorch, TensorFlow, or similar.
- Experience with semantic mapping.
- Experience with image processing techniques and computer vision fundamentals.
Responsibilities
- Develop machine learning models that revolutionize our customers’ businesses.
- Treeswift develops machine learning algorithms that upend the cost and accuracy of field work for energy infrastructure.
- Our machine learning model development focuses on two primary areas: (a) LiDAR point cloud models to classify and segment landscapes and infrastructure and (b) image models to derive vegetation attributes such as species and health.
- In this role you will be responsible for bringing innovative ideas and rapid execution to new and existing models.
- Create a best-in-class feedback loop to accelerate model development.
- You will improve Treeswift’s ability to assess model performance and adapt to new operating conditions at scale.
- In this role you will be expected to bring prior experience with commercial machine learning model development and deployment to help Treeswift cost-effectively scale its technology to serve a growing number of customers and use cases.
Other
- This is a full-time, hybrid/2-day a week in person role in our NYC office.
- Exceptional communication and collaboration skills.
- 5+ years of professional experience or 3+ years with an advanced degree.
- Mission first.
- Truth seeking.
