Machine Learning Engineer

Machine Learning Engineer About Treeswift: In the face of rising threats like severe storms and wildfires, increasing pressure on affordability, and unprecedented demands for system expansion, Treeswift empowers energy companies to modernize their field work to meet the unprecedented growth and challenges ahead. To accomplish our mission we deploy our sensors into our customers' field operations, typically on backpacks or vehicles. The resulting trove of LiDAR and imagery data is processed through our AI models to deliver actionable analytics through our web platform. To date, our technology has enabled utilities to reduce wildfire, regulatory and outage risk from vegetation, avoid delays and cost overruns in new construction, and accelerate recovery from severe storms. After starting our work with utilities in June 2024, we are now working with three of the five largest utilities in the United States and are rapidly expanding across new customers and use cases. To tackle this challenge we are bringing together a team of mission-driven experts with deep industry experience in robotics (Penn, Caltech, CMU) and enterprise software development (Palantir, Stripe, Oracle, MongoDB). We have raised funding from leading investors including Penny Pritzker’s Inspired Capital. Treeswift is headquartered in lower Manhattan, and maintains an office in Philadelphia. We also have some customer-facing team members based closer to our customer sites (i.e. Bay Area). We hope you join us on this journey! About the Role: Treeswift is seeking a highly skilled and motivated engineer to join our team. You will play a pivotal role in developing and deploying state-of-the-art machine learning solutions to advance our mission. We are looking for an exceptional candidate with a proven track record of training and deploying models in a commercial setting. If you are a passionate and experienced engineer eager to contribute to the future of distributed infrastructure management we encourage you to apply. This is a full-time, hybrid/2-day a week in person role in our NYC office. Key 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. In the course of development, you will collaborate closely with other teams (product, operations etc…) and have an opportunity to interact with end-users. - 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. Treeswift’s cutting edge model development involves significant investment in a proprietary dataset to train our models. - Help Treeswift 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. You will be responsible for enabling effective collaboration on model development within the engineering team, and you will contribute to efforts to ensure reliable and robust performance of models in production. Required Skills - 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, Tens ... (truncated, view full listing at source)