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Senior Staff Machine Learning Engineer - DevOps

ServiceNow · Santa Clara, CA · posted 3 days ago

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311
Certified filings · by ServiceNow, FY2026 Q2
$239,841
Median filed wage · for “Senior Staff Software Engineer” · 11 filings

Source: US DOL Office of Foreign Labor Certification, LCA disclosure data, FY2026 Q2. Government data is published roughly one quarter in arrears.

This advert was matched to Senior Staff Software Engineer, a job title ServiceNow has itself sponsored.

The figure above is not this job’s salary. It is what ServiceNow reported to the US Department of Labor for the closest role it has sponsored. A filing history means this employer has sponsored before — it is not a promise that this opening carries sponsorship, and not an offer of pay. Check the advert and ask the employer.

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The role, as ServiceNow describes it

What you get to do in this role:

Please note that this role requires you to be in our Santa Clara office for two days per week. About the team - The AI Services Platform Group at ServiceNow is a customer-focused innovation group building intelligent software and smart user experiences using existing and latest advanced technologies to enable end-to-end, industry-leading work experiences for customers. We are a group of researchers, applied scientists, engineers, and product managers with a dual mission. We build and evolve the AI platform, and partner with teams to build products and end-to-end AI-powered work experiences. In equal measure, we lay the foundations, research, experiment, and de-risk AI technologies that unlock new work experiences in the future. We are seeking a Senior Staff Machine Learning Engineer (DevOps) to lead the architecture, optimization, and operational excellence of our AI inference platform. You will own the end-to-end inference lifecycle—from onboarding cutting-edge models to deploying optimized inference engines in production across multiple backends on Kubernetes infrastructure. You'll also architect the intelligent gateway layer using Envoy and ext_proc to enforce access control, provide observability, and enable advanced request routing. This role combines deep technical expertise in GPU compute, LLM APIs, inference frameworks, containerization, orchestration, and API gateway architecture with a bias toward pragmatic engineering and measurable performance impact.

To be successful in this role you have: - Expertise in Go or Python, OOP, Design Patterns, time and space-efficient algorithms - Experience building new products that use challenging algorithms - Expertise in coding efficient, object-oriented, modularized and quality software - Knowledge of core AI/ML techniques and algorithms - Knowledge of unit testing, profiling, and code tuning

DevOps: - Deploy, scale, and operate services in production Kubernetes environments, including Helm-based deployments and CI/CD pipelines that make releases repeatable and safe to roll back. - Own observability for what you build — meaningful metrics, useful logs, real tracing, and alerts that fire on customer impact rather than on noise. - Debug and resolve production incidents independently, participate in on-call, run root-cause analysis, and operate against defined service level objectives. AI skills

Artificial intelligence strategy is a critical skill at Experienced proficiency for IC5 — it applies to how you build and to what you build. - Confident use of AI coding assistants such as GitHub Copilot or Cursor, paired with the critical eye to review AI-generated code as rigorously as any other — catching logic errors, security anti-patterns, and missed edge cases rather than treating model output as production-ready. - AI-assisted debugging and trace analysis, and a clear understanding of the data privacy rules governing what goes into a prompt. Mandatory minimum - 8+ years of Backend software engineering experience - 4+ years of designing and operating distributed systems - 3+ years of Kubernetes in production, including Helm and CI/CD Bachelor’s degree in computer science, software engineering, or a closely related technical field required.

A master’s degree may offset up to one year of the experience minimum. Equivalent practical experience is considered where technical depth is clearly demonstrable. For positions in this location, we offer a base pay of $201,300 - $352,300 , plus equity (when applicable), variable/incentive compensation and benefits. Sales positions generally offer a competitive On Target Earnings (OTE) incentive compensation structure. Please note that the base pay shown is a guideline, and individual total compensation will vary based on factors such as qualifications, skill level, competencies, and work location. We also offer health plans, including flexible spending accounts, a 401(k) Plan with com

Read the full advert and apply on ServiceNow’s site →

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