aidashinc · Palo Alto, California, United States · Palo Alto, California, United States
<div class="content-intro"><p><strong>About AiDASH</strong><br><br><span data-teams="true">AiDASH is leading the PreventionFirst™movement for electric utilities and transforming grid resilience through its pioneering platform that unifies vegetation, asset, storm, and wildfire intelligence. Powered by SatelliteFirst™ Inspection & Monitoring, AiDASH delivers comprehensive visibility across the entire grid at the right frequency and budget, using the right data modality. More than 200 customers trust AiDASH to keep the lights on, spend where it counts, and defend every decision, Securing Tomorrow across every mile of the grid.</span> Learn more at <a href="https://www.aidash.com." target="_blank">www.aidash.com.</a></p> <p><span data-contrast="auto">The PreventionFirst movement is growing, and so is the recognition behind it. In 2026, Forbes named AiDASH one of America's Best Startup Employers for the 4th consecutive year, and TIME included AiDASH among America's Top GreenTech Companies for the 3rd year in a row. </span><a href="https://www2.deloitte.com/us/en/pages/technology-media-and-telecommunications/topics/north-america-technology-fast-500.html?utm_source=bngaiwebsite&utm_medium=referral&utm_campaign=evolve-banner"><span data-contrast="none"><span data-ccp-charstyle="Hyperlink">Deloitte Technology Fast 500</span></span></a><span data-contrast="auto">™ ranked AiDASH No. 12 in the San Francisco Bay Area, and No. 59 overall in their selection of the top 500 for 2024.</span><span data-ccp-props="{"335551550":0,"335551620":0}"> </span></p> <p><span data-contrast="auto">Join us in Securing Tomorrow Together!</span><span data-ccp-props="{"335551550":0,"335551620":0}"> </span></p></div><p><strong><span data-contrast="none">The Role</span></strong><span data-ccp-props="{}"> </span></p> <p><span data-contrast="auto">Our satellite and AI-powered products are changing how utilities see and protect the grid, and we're gearing up for aggressive customer growth over the next two years. That growth runs on AI at scale. <strong>We're building a brand-new Data Inference AI Pipeline team to deliver it, and we're looking for a Staff MLOps Engineer to architect its operational backbone from the very first line of infrastructure code.</strong></span><strong><span data-ccp-props="{"335559738":240,"335559739":240}"> </span></strong></p> <p><span data-contrast="auto">As the <strong>very first engineer on this team</strong>, you'll start with a blank canvas and a rare chance to build something that lasts. You'll shape how our models are deployed, how the pipeline scales and recovers under load, and what it costs to run. Just as importantly, you'll help define the culture, engineering standards, and ways of working that every future teammate inherits. This is a hands-on, high-leverage individual contributor role: your decisions will set the foundation the entire team builds on, and you'll be the go-to technical authority on MLOps as the team grows. You'll report to the Director of Engineering for the Data Inference AI Pipeline team. </span><span data-ccp-props="{"335559738":240,"335559739":240}"> </span></p> <p><span data-contrast="auto">Our pending acquisition by Schneider Electric will accelerate our mission as we bring our combined offering to our joint customer base, and the infrastructure you build will power outcomes at an even greater scale.</span></p> <p><strong><span data-contrast="none">Location: </span></strong><span data-contrast="none">This is a hybrid role based in Palo Alto, CA, requiring 2 days per week in the office.</span><span data-ccp-props="{"335557856":16777215,"335559738":240,"335559739":240}"> </span></p> <p><strong><span data-contrast="none">How you'll make an impact:</span></strong><span data-ccp-props="{"335557856":16777215,"335559738":240,"335559739":240}"> </span></p> <p><strong><span data-contrast="auto">Deployment</span></strong><span data-ccp-props="{"335559738":240,"335559739":240}"> </span></p> <ul> <li><span data-contrast="auto">Own the model deployment pipeline end-to-end: packaging, versioning, rollout, and rollback for ML models moving from training to production</span><span data-ccp-props="{"335559739":0}"> </span></li> <li><span data-contrast="auto">Build and maintain deployment infrastructure on SageMaker (endpoints, batch transform, multi-model/multi-container hosting), and evaluate where alternatives such as self-hosted serving or other managed options are a better fit</span><span data-ccp-props="{"335559739":0}"> </span></li> <li><span data-contrast="auto">Set the CI/CD pattern for model releases, including automated testing, staged rollout, and canary/shadow deployments</span><span data-ccp-props="{"335559739":0}"> </span></li> </ul> <p><strong><span data-contrast="auto">Scalability & elasticity</span></strong><span data-ccp-props="{"335559738":240,"335559739":240}"> </span></p> <ul> <li><span data-contrast="auto">Design inference infrastructure that scales seamlessly with real-time and batch demand</span><span data-ccp-props="{"335559739":0}"> </span></li> <li><span data-contrast="auto">Righ