Senior (DevOps) Machine Learning Engineer - Federal

ServiceNow•Santa Clara, CA

19d•$161,300 - $274,200

About The Position

The Senior Machine Learning Engineer will join ServiceNow’s Advanced Technology Group (ATG), a customer-focused innovation group of researchers, applied scientists, engineers, and product managers. ATG builds and evolves the AI platform, partners with teams on AI-powered products and work experiences, and researches and de-risks technologies for future applications. The role builds AI and machine-learning solutions that improve enterprise service user experiences and workflow efficiency. The engineer develops cloud-based AI/ML solutions and collaborates with developers, product managers, quality engineers, and product owners. They own code from design through implementation, testing, and delivery, while also deploying and operating services in production Kubernetes environments. The position includes responsibility for service observability, production incident response, on-call participation, root-cause analysis, and meeting defined service level objectives.

Requirements

Expertise in Go or Python, design patterns, and time- and space-efficient algorithms.
Experience building new products that use challenging algorithms.
Expertise in writing efficient, object-oriented, modularized, high-quality software.
Knowledge of core AI/ML techniques and algorithms.
Knowledge of unit testing, profiling, and code tuning.
Experience deploying, scaling, and operating services in production Kubernetes environments, including Helm-based deployments and CI/CD pipelines.
Ability to own service observability, debug and resolve production incidents, participate in on-call, perform root-cause analysis, and operate against defined service level objectives.

Nice To Haves

Confident use of AI coding assistants such as GitHub Copilot or Cursor, with the ability to rigorously review generated code for logic errors, security anti-patterns, and missed edge cases.
Experience with AI-assisted debugging and trace analysis, and understanding of data privacy rules governing prompt content.

Responsibilities

Build cloud-based AI/ML solutions for intelligent enterprise services.
Collaborate with developers, product managers, and quality engineers to produce quality software.
Work with product owners to understand detailed requirements.
Own code through design, implementation, testing, and delivery of high-quality solutions.
Deploy, scale, and operate services in production Kubernetes environments, including Helm-based deployments and CI/CD pipelines.
Build and maintain meaningful metrics, useful logs, tracing, and customer-impact-focused alerts for services.
Independently debug and resolve production incidents.
Participate in on-call rotations and root-cause analysis, and operate against defined service level objectives.