Staff MLOps Engineer

The posting, as AiDASH, Inc. wrote it

About AiDASH

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. Learn more at www.aidash.com.

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. Deloitte Technology Fast 500 ™ ranked AiDASH No. 12 in the San Francisco Bay Area, and No. 59 overall in their selection of the top 500 for 2024.

Join us in Securing Tomorrow Together!

The Role

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. 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.

As the very first engineer on this team , 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.

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.

Location: This is a hybrid role based in Palo Alto, CA, requiring 2 days per week in the office.

How you'll make an impact

Deployment

• Own the model deployment pipeline end-to-end: packaging, versioning, rollout, and rollback for ML models moving from training to production
• 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
• Set the CI/CD pattern for model releases, including automated testing, staged rollout, and canary/shadow deployments

Scalability & elasticity
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• A background in a regulated or enterprise B2B domain such as utilities, energy, infrastructure, healthcare, or finance
• Relevant AWS/Kubernetes certifications or open-source MLOps tooling contributions

What you'll love

• Comprehensive Medical, Dental, and Vision Coverage: 100% coverage for employees and 80% for their spouses and children
• Health Reimbursement Account (HRA): 100% funded by AiDASH to cover medical deductibles
• 401(k) Plan: Begin contributing after two months of employment to prepare for your future. Currently, no company match is offered
• Parental Leave: Supportive parental leave with 16 weeks for primary caregivers and 4 weeks for secondary caregivers
• Generous Vacation Policy: Accrue 20 vacation days per year, plus enjoy an additional flex holiday to celebrate whatever feels most important to you
• Winter Break: From December 25th through January 1st, we give everyone time off to recharge and enjoy time with family and friends!

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 annual pay range of $230,000 to $270,000 for this full-time position, which includes a base salary and bonus based on performance. This range reflects the anticipated annual pay range (base + bonus) 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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