Principal Machine Learning Engineer
Company websiteservicenow.com (ServiceNow, opens in new tab)
Base salary $240,100 to $420,200
Employer-published annual base salary, USD. Advertised base range in Santa Clara, CA
You apply on the employer's own site. Six Figure Work does not handle applications.
- LocationSanta Clara, CA
- WorkplaceHybrid
- Status at last checkSource accepting applications when checked
- Last checked (48 min ago) · observed since
About this job
Company Description
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.
Job Description
In this role you will play a key role in defining and building the cloud-native infrastructure that powers ServiceNow's next generation of Agentic AI and conversational experiences. As a Principal Engineer, you will drive architecture and technical strategy across multiple engineering organizations while remaining deeply hands-on in solving complex platform and scalability challenges.
- Lead the technical direction, architecture, and evolution of cloud-native platform services supporting Agentic AI initiatives.
- Drive the design and implementation of scalable Kubernetes-based infrastructure that supports AI/ML and conversational workloads at enterprise scale.
- Partner with engineering, infrastructure, product, and platform teams to modernize critical services and accelerate the transition to next-generation architectures.
- Design and build highly available, secure, observable, and resilient distributed systems supporting mission-critical customer workloads.
- Establish architectural standards, engineering best practices, and platform patterns that can be leveraged across multiple product teams.
- Drive automation across infrastructure provisioning, deployment pipelines, service operations, monitoring, and incident response.
- Evaluate and adopt emerging technologies in cloud-native infrastructure, Kubernetes, AI platforms, and distributed systems.
- Mentoring senior engineers and providing technical leadership through influence across organizational boundaries.
- Lead architecture reviews and provide guidance on scalability, reliability, performance, security, and operational excellence.
- Partner closely with teams developing AI-powered experiences to ensure underlying infrastructure can support future growth and innovation.
- Work with stakeholders across the organization to balance long-term platform investments with near-term product delivery goals.
- Own technical initiatives from concept through production deployment while helping shape the future direction of ServiceNow's Agentic AI platform.
Qualifications
To be successful in this role, you have:
- 15+ years of experience building large-scale distributed systems, cloud platforms, infrastructure services, or enterprise SaaS products.
- Deep expertise in Java, Go, Python, or similar systems programming languages.
- Proven experience designing, building, and operating highly scalable cloud-native architectures.
- Expert knowledge of Kubernetes, containers, orchestration platforms, and modern cloud infrastructure.
- Experience building platform services used across multiple engineering teams and products.
- Strong understanding of distributed systems principles, including resiliency, fault tolerance, scalability, performance optimization, and observability.
- Experience with AWS, Azure, or Google Cloud at large scale.
- Expertise in CI/CD, infrastructure automation, GitOps, Terraform, Helm, ArgoCD, or comparable technologies.
- Strong software engineering fundamentals including object-oriented design, system design, architecture patterns, and performance optimization.
- Experience leading technical strategy and influencing architecture across multiple organizations without direct authority.
- Demonstrated track record building new platform capabilities from concept through large-scale production adoption.
- Strong communication skills with the ability to explain technical tradeoffs to engineering and executive leadership.
Preferred Qualifications
- Experience building infrastructure for AI/ML, generative AI, agentic systems, or conversational platforms.
- Experience supporting GPU workloads, model serving, inference platforms, or AI runtime environments.
- Experience with internal developer platforms, platform engineering, SRE, or cloud infrastructure organizations.
- Knowledge of multi-agent architectures, orchestration platforms, workflow engines, or large-scale automation systems.
- Experience with modern observability platforms including OpenTelemetry, Prometheus, Grafana, Datadog, or equivalent technologies.
- Experience modernizing legacy architectures into cloud-native distributed services.
For positions in this location, we offer a base pay of $240,100 - $420,200, 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.
Additional Information
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.
From Fortune. ©2026 Fortune Media IP Limited. All rights reserved. Used under license.
Source: ServiceNow on SmartRecruiters · View original posting (opens in new tab)
Pay in context
This role's base floor ($240,100) is above 79% of the 1,469 Data & ML roles in California listed on this site; 2 others list the same floor. Their median floor is $190,000; the middle half runs from $160,000 to $229,900.
Only jobs on this site count, and each one publishes a base salary of $100,000 or more, so this compares six-figure jobs with each other, not with the whole market. Computed Nov 6, 2026.
This listingPrincipal Machine Learning Engineer$240,100 to $420,200
Principal Data Platform Software Engineer (Database Operations)$240,100 to $420,200
Principal Machine Learning Engineer$240,100 to $420,200
GVP, Enterprise Verticals Sales US (Manufacturing, Transportation & Energy)$230,950 to $392,600
Area VP, Solution Consulting$225,825 to $372,600
Senior Director, Product Creative Direction$254,500 to $445,400
Senior Director Product Analytics$254,500 to $445,400
Chart as a table
| Role | Published base |
|---|---|
| Principal Machine Learning Engineer (this listing) | $240,100 - $420,200 |
| Principal Data Platform Software Engineer (Database Operations) | $240,100 - $420,200 |
| Principal Machine Learning Engineer | $240,100 - $420,200 |
| GVP, Enterprise Verticals Sales US (Manufacturing, Transportation & Energy) | $230,950 - $392,600 |
| Area VP, Solution Consulting | $225,825 - $372,600 |
| Senior Director, Product Creative Direction | $254,500 - $445,400 |
| Senior Director Product Analytics | $254,500 - $445,400 |
Observed changes
- First observed on the employer's board
- Began meeting the published-salary criteria
- Observed since
- Employer-stated posting date
- 2026-10-20
Where this pay comes from
Location as the employer wrote it: Santa Clara, California, United States
For positions in this location, we offer a base pay of $240,100 - $420,200, plus equity (when applicable), variable/incentive compensa
- Method
- Employer text, read with fixed rules and re-verified
- Checked
- Rule set
- us-base-v2
The pay passage appears in the employer's own job text. Fixed, deterministic rules located it, and the passage below was checked against the stored copy of the posting.
What we verified
- The pay figures come from the employer's own listing, quoted exactly above.
- The pay is an annual base salary in US dollars with a minimum of at least $100,000.
- The role was publicly listed on the employer's job board when last checked.
We do not verify what the employer will actually offer, whether the employer is still recruiting for the role, or anything beyond what the employer published. Full methodology.
