ML Ops Engineer

Overview

At Zebra, we are a community of innovators who come together to create new ways of working. United by curiosity and a culture of caring, we develop smart solutions that anticipate our customer’s and partner’s needs and solve their challenges. Being part of Zebra Nation means you are seen, heard, valued, and respected.

Drawing from our unique perspectives, we collaborate to deliver on our purpose. Here you are part of a team pushing boundaries today to redefine the work of tomorrow for organizations, their employees, and those they serve. You’ll have opportunities to learn and lead in a forward-thinking environment, defining your path to a fulfilling career while channeling your skills toward causes you care about—locally and globally.

Come make an impact every day at Zebra.

What We're Looking For

Analyzes, designs, develops, and maintains software for the organization’s products and systems. Performs system integration of software and hardware to ensure consistency, reliability, and throughput. Develops, validates, and tests software structures and user documentation. Operates with minimal supervision and exercises significant latitude in determining the objectives of assignments, contributing to complex and high-impact projects.

Essential Duties and Responsibilities

Design and build production-grade containerized environments using Kubernetes, Open. Shift, and Docker to support distributed edge AI backends. Design and maintain resilient, scalable cloud infrastructure across AWS and Open. Stack tailored for high-throughput edge AI workloads. Manage advanced GPU resource allocation, scheduling, and ML pipeline orchestration tools (e.

g., Kubeflow) on Kubernetes clusters. Establish resilient microservices architectures, ensuring platform high availability, fault tolerance, and security compliance. Proactively own core platform infrastructure to boost operational maturity, eliminate system downtime risks, and streamline platform-wide deployment velocity.

Deploy a platform-specific runtime backed server (Triton/TensorRT/QNN/SNPE). Job Requirements: Bachelors Degree or Advanced Degree in Computer Science, Software Engineering, or a related engineering discipline

• 6+ years of relevant work experience with a Bachelors Degree, 3+ years of relevant experience with an Advanced Degree Equivalency: Equivalent work experience will be considered in lieu of a degree Key Skills and Competencies: Design and build production-grade containerized environments using Kubernetes, Open. Shift, and Docker to support distributed edge AI backends. Design and maintain resilient, scalable cloud infrastructure across AWS and Open. Stack tailored for high-throughput edge AI workloads. Manage advanced GPU resource allocation, scheduling, and ML pipeline orchestration tools (e.g., Kubeflow) on Kubernetes clusters. Establish resilient microservices architectures, ensuring platform high availability, fault tolerance, and security compliance. Proactively own core platform infrastructure to boost operational maturity, eliminate system downtime risks, and streamline platform-wide deployment velocity. Deploy a platform-specific runtime backed server (Triton/TensorRT/QNN/SNPE).

Benefits

We understand the importance of work-life balance and wellbeing, which is why we offer flexibility for our teams including: hybrid work, adaptable hours, Summer Flex Fridays, Focus Fridays, and an annual companywide well-being day to promote revitalization and success. Job Posting Statement: To protect candidates from falling victim to online fraudulent activity involving fake job postings and employment offers, please be aware our recruiters will always connect with you via @zebra.

com email accounts. Applications are only accepted through our applicant tracking system and only accept personal identifying information through that system. Our Talent Acquisition team will not ask for you to provide personal identifying information via e-mail or outside of the system. If you are a victim of identity theft contact your local police department.

AI Technology Statement: Zebra Technologies leverages AI technology to evaluate job applications using objective, job-relevant criteria. This approach enhances efficiency and promotes fairness in the hiring process. However, every decision regarding interviews and hiring is made by our dedicated team, because we believe people make the best decisions about people.

For more on how we use technology in hiring and how we process applicant data, see our Zebra Privacy Policy .