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Staff MLOps Engineer

AiDASH, Inc.Palo Alto, California, United StatesR&D
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Salary
$230K to $270K
Job type
Full-time
Experience
Senior · 7+ yrs
Posted
10 Oct 2026
Status
Open · checked 7d ago

About this role

This Staff MLOps Engineer position suits an experienced software or machine learning professional looking to build and lead a brand-new data inference AI pipeline infrastructure from scratch. The role is a hybrid position based in Palo Alto, California, requiring two days per week in the office.

Role Overview

AiDASH, Inc. is seeking a Staff MLOps Engineer to architect the operational backbone of its new Data Inference AI Pipeline team. As the first engineer on this team, the individual will operate in a hands-on individual contributor role to set the foundation for model deployment, scalability, cost optimization, and resilience. The position involves partnering with Data Science and Web Application teams to support satellite and AI-powered utility products during a period of aggressive customer growth.

Key Responsibilities

Own the model deployment pipeline end-to-end, covering packaging, versioning, rollout, and rollback for machine learning models moving from training to production.
Build and maintain deployment infrastructure on SageMaker, while evaluating alternatives such as self-hosted serving or other managed options.
Set CI/CD patterns for model releases, including automated testing, staged rollouts, and canary or shadow deployments.
Design inference infrastructure that scales seamlessly with real-time and batch demand, right-sizing compute resources for each workload.
Own the cost-per-inference metric by instrumenting, reporting, and driving down costs as volume scales through autoscaling policies and spot or on-demand mixes.
Design for graceful degradation, failover across regions and availability zones, disaster recovery procedures, and regular failure-injection exercises.
Build monitoring, alerting, and on-call runbooks for model-serving infrastructure covering drift, latency service level objectives, and error rates.
Partner with Data Science to bring new models into production and collaborate with the Web Application team to align latency and reliability expectations for customer-facing features.

Requirements

Seven to ten plus years of experience in software or machine learning engineering, including at least three years focused specifically on MLOps or machine learning infrastructure.
Hands-on production experience with AWS SageMaker or an equivalent managed machine learning platform for model deployment and serving.
Proven track record of designing systems for elasticity, autoscaling, cost optimization, and failover resilience at production scale.
Strong expertise in containerization and orchestration tools like Docker and Kubernetes.
Experience building CI/CD tailored for machine learning workloads, including model versioning and automated testing and rollout.
Ability to instrument and own cost and performance metrics for managed infrastructure.
Experience setting technical direction as a Staff-level individual contributor and building buy-in across cross-functional engineering teams.

Nice to Have

Experience with large imagery, video, 3D sensor, point-cloud data pipelines, or multimodal data such as geospatial and time-series data.
Experience building MLOps practices from scratch on a new team.
Familiarity with model monitoring and drift-detection tooling, along with GPU cost-optimization techniques including quantization and batching.
Background in a regulated or enterprise B2B domain like utilities, energy, infrastructure, healthcare, or finance.
Relevant AWS or Kubernetes certifications and open-source MLOps tooling contributions.

Skills and Tools

AWS SageMaker
Docker
Kubernetes
CI/CD tooling
Model versioning systems
Cloud compute options including CPU, GPU, and Inferentia

Salary and Benefits

Annual salary and performance bonus range of $230,000 to $270,000 for this full-time position.
Comprehensive medical, dental, and vision coverage offering 100 percent coverage for employees and 80 percent for spouses and children.
Employer-funded Health Reimbursement Account to cover medical deductibles.
401(k) plan eligibility after two months of employment.
Supportive parental leave offering 16 weeks for primary caregivers and 4 weeks for secondary caregivers.
Generous vacation policy of 20 accrued vacation days per year, plus a flex holiday and a company-wide winter break from December 25th through January 1st.

About the Company

AiDASH leads the PreventionFirst movement for electric utilities, providing a pioneering platform that unifies vegetation, asset, storm, and wildfire intelligence. Powered by SatelliteFirst Inspection and Monitoring, the company delivers comprehensive grid visibility to over 200 customers. Recognized by Forbes, TIME, and Deloitte, AiDASH is preparing for a pending acquisition by Schneider Electric to expand its offerings.

How to Apply

Candidates should apply on the official AiDASH careers page.

Skills and tech stack

AWS SageMakerDockerKubernetesAWS InferentiaAWS TrainiumAWSMLOps

Questions candidates ask

What is the work location and office attendance policy?

This is a hybrid role based in Palo Alto, California, requiring employees to work from the office two days per week.

What is the salary range for the Staff MLOps Engineer role?

The position offers an annual pay range of $230,000 to $270,000, which includes a base salary and a performance-based bonus.

How many years of experience are required?

Candidates must have 7 to 10 plus years of experience in software or machine learning engineering, with at least 3 years focused specifically on MLOps or machine learning infrastructure.

What health and insurance benefits are provided?

AiDASH offers comprehensive medical, dental, and vision coverage with 100 percent coverage for employees and 80 percent for spouses and children, alongside a 100 percent employer-funded Health Reimbursement Account.

Is there a company match for the 401(k) plan?

Employees can begin contributing to the 401(k) plan after two months of employment, but there is currently no company match offered.

Ready to apply?

The application is on the official AiDASH, Inc. careers page.

Apply on company site