Senior Staff Machine Learning Engineer - DevOps

It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. That moment inspired Fred to build a company that could do that for everyone—freeing people from busywork so they could focus on meaningful work. Today, ServiceNow is the AI control tower for business reinvention. Our ServiceNow AI platform brings together any AI, any data, and any workflow— helping 85% of the Fortune 500® work smarter, faster, and better. We're building an AI-native culture where technology and talent are unstoppable together. And we're just getting started.

Join us to put AI to work for people.

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 company match, ESPP, matching donations, a flexible time away plan and family leave programs. Compensation is based on the geographic location in which the role is located and is subject to change based on work location.

Work Personas

We approach our distributed world of work with flexibility and trust. Work personas (flexible, remote, or required in office) are categories that are assigned to ServiceNow employees depending on the nature of their work and their assigned work location. Learn more here. To determine eligibility for a work persona, ServiceNow may confirm the distance between your primary residence and the closest ServiceNow office using a third-party service.

Equal Opportunity Employer

ServiceNow is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, national origin, age, disability, gender identity,  veteran status, or any other category protected by law. In addition, all qualified applicants with arrest or conviction records will be considered for employment in accordance with legal requirements.  

Accommodations

We strive to create an accessible and inclusive experience for all candidates. If you require a reasonable accommodation to complete any part of the application process, or are unable to use this online application and need an alternative method to apply, please contact [email protected] for assistance. 

Export Control Regulations

For positions requiring access to controlled technology subject to export control regulations, including the U.S. Export Administration Regulations (EAR), ServiceNow may be required to obtain export control approval from government authorities for certain individuals. All employment is contingent upon ServiceNow obtaining any export license or other approval that may be required by relevant export control authorities. 

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