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 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.

In just a year and a half since our first utility pilot we are working with three of the five largest utilities in the United States and rapidly expanding across new customers and use cases. To tackle this challenge we are bringing together a team of mission-driven experts from with deep industry experience in robotics (UPenn, Caltech, CMU) and enterprise software development (Palantir, Stripe, Oracle).

We have raised from leading investors including Penny Pritzker’s Inspired Capital. We hope you’ll join us on this journey

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.

• 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 eswift’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.

• 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, Tensor Flow, or similar.
• Excellent problem-solving and analytical abilities.
• Exceptional communication and collaboration skills.

• Experience with semantic mapping.
• Experience with image processing techniques and computer vision fundamentals.
• Experience with one or more of:
  Sensor Fusion, SLAM, Visual Odometry.
• Building and using cloud-based training and inference pipelines.
• 5+ years of professional experience or 3+ years with an advanced degree.
• Experience…