The problem: Every minute matters in fire response. As climate change amplifies the intensity of wildfires—with longer fire seasons, dryer fuels, and faster winds—new ignitions spread faster and put more communities at risk. Today, most wildfires are detected by bystanders and reported via 911, meaning it can take hours to detect a fire, verify its exact location and size, and dispatch first responders. Fire authorities need a faster way to detect, confirm, and pinpoint fires, so that they can quickly respond—preventing small flare-ups from becoming devastating infernos.
About Pano: Pano is a venture-backed early stage climate tech startup that is the leader in wildfire early detection, leveraging the latest advancements in IoT, AI, satellites, and SaaS software to deliver actionable intelligence to customers. Pano leverages mountaintop cameras and satellites to detect the first traces of smoke and put real-time fire images in the hands of first responders to speed up containment. Pano is already partnering with major utilities, fire authorities, and government agencies in California, Colorado and Oregon, with plans to expand to other western states and Australia this year. Recent media coverage includes articles from the San Francisco Chronicle and TD World, a leading industry publication.
Our team is composed of seasoned technology professionals from companies such as Cisco, Apple, and Nest. Headquartered in San Francisco with an office and factory in the Mission District, our hybrid team works from locations around the world. Founded in mid-2020, we’ve raised over $8M from leading VC funds and prominent angel investors, including the CEOs of Gitlab, HomeLight, and People.AI.
Pano is looking for an experienced Computer Vision (CV) expert to develop and execute Pano’s roadmap for our smoke detection CV model(s) for DayTime Panoramic Camera, NightTime IR Camera and Satellite images. He/she is responsible for developing CV models for early detection of Fire/Smoke in different types of cameras (Panoramic, IR and Satellite), maintaining database of fire/smoke labels, working with labellers and data engineering for implementing Active Learning pipelines, preprocessing and postprocessing to reduce the FP and FN and adopt the models for different geographic locations/landscapes and weather conditions. Ideal candidates have deep expertise in DL based computer vision, as well as experience with traditional computer vision techniques, time series, synthetic data, and near-real-time production inference. Position is remote but company meetings are scheduled for the Pacific time zone. This individual will report to Pano’s Engineering Manager of ML.
Pano is an equal opportunity employer committed to recruiting and supporting our team-members regardless of where they come from. We do not discriminate on the basis of race, color, religion, gender, gender identity or expression, sexual orientation, national origin, genetics, disability, age, or veteran status.
Interested candidates should forward a resume or a link to your LinkedIn profile to ML_Hiring@pano.ai.