About AiDASH
AiDASH is making critical infrastructure industries climate-resilient and sustainable with satellites and AI. Using our full-stack SaaS solutions, customers in electric, gas, water utilities, transportation, and construction are transforming asset inspection and maintenance - and complying with biodiversity net gain mandates and carbon capture goals. AiDASH exists to safeguard critical infrastructure and secure the future of humanAIty. Learn more at
We are a Series C climate tech startup backed by leading investors, including Shell Ventures, National Grid Partners, G2 Venture Partners, Duke Energy, Edison International, Lightrock, Marubeni, among others. We have been recognized by Forbes two years in a row as one of “America’s Best Startup Employers.” We are also proud to be one of the few climate software companies in Time Magazine’s “America’s Top GreenTech Companies 2024”. recently ranked us at No. 12 among San Francisco Bay Area companies, and No. 59 overall in their selection of the top 500 for 2024.
Join us in Securing Tomorrow!
The Role
We are looking for a Staff Machine Learning Engineer with deep expertise in aerial LiDAR processing and 3D computer vision . In this role, you will be responsible for designing advanced ML models - including custom CNN and Transformer architectures - for large-scale 3D point clouds and multi-modal remote sensing data.
We are proud to be an equal-opportunity employer. We are committed to embracing diversity and inclusion in our hiring practices, and we promote a work environment where everyone, from any race, color, religion, sex, sexual orientation, gender identity, or national origin, can do their best work.
We offer a competitive base pay range for this full-time position, which is between $190,000 and $230,000 per year. This range reflects the anticipated base salary for new hires. We strive to ensure our compensation packages are equitable and aligned with industry standards. Your recruiter can share more about compensation during the hiring process.
We are committed to providing an inclusive and accessible interview experience for all candidates. Please let us know if you require any accommodation during the interview process, and we will make every effort to meet your needs.
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