About the job
About AiDASH
AiDASH is a pioneering enterprise AI firm that specializes in providing vegetation risk intelligence for electric utilities. Utilizing our exclusive VegetationAI™ technology, we deliver a comprehensive remote grid inspection and monitoring platform that adopts a SatelliteFirst approach to identify and mitigate vegetation and other hazards impacting the grid. Our proactive strategy minimizes wildfire risks and reduces the effects of storms, enabling over 140 utilities to cut costs, enhance reliability, and lower liabilities across their infrastructure. AiDASH is dedicated to protecting critical utility systems and ensuring a sustainable future for humanity. Discover more at www.aidash.com.
As a Series C growth company, we are supported by esteemed investors, including Shell Ventures, National Grid Partners, G2 Venture Partners, Duke Energy, and others. We are honored to be recognized by Forbes for two consecutive years as one of “America’s Best Startup Employers” and to feature in Time Magazine’s “America’s Top GreenTech Companies 2024.” Recently, Deloitte Technology Fast 500™ ranked us No. 12 among companies in the San Francisco Bay Area and No. 59 overall among their top 500 for 2024.
Join us in Securing Tomorrow!
The Role
We are seeking a highly experienced Staff Machine Learning Engineer to define and expand the core of our production ML ecosystem. In this capacity, you will design high-performance ML systems that drive our geospatial intelligence platform, converting extensive satellite and aerial imagery into actionable insights. Your responsibilities will encompass complete ownership—from model deployment and MLOps to infrastructure design—while collaborating closely with data science, platform engineering, and product teams to deliver dependable, scalable, and cost-effective ML solutions. If you excel at the intersection of advanced technical knowledge, system architecture, and cross-functional teamwork, this opportunity is for you.
How You'll Make an Impact:
ML System Architecture & Production Deployment
- Design, build, and maintain end-to-end ML pipelines for batch processing...

