ServiceNow

Senior Staff Machine Learning Engineer

Senior Staff ML Engineer at ServiceNow (Santa Clara, CA). Design AI infrastructure & platforms using Python/GoLang/Java. 6-8yrs dev exp, Kubernetes/DevOps expertise required. Health, 401k, ESPP, flexible PTO.

ServiceNow Role Type:
Department - JobBoardly X Webflow Template
Implementer
ServiceNow Modules:
Department - JobBoardly X Webflow Template
DevOps
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Predictive Intelligence
ServiceNow Certifications (nice to have):

Job description

Date - JobBoardly X Webflow Template
Posted on:
 
December 1, 2025

ServiceNow is a global market leader bringing innovative AI-enhanced technology to over 8,100 customers. As a Senior Staff Machine Learning Engineer, you will contribute to the design, development, and implementation of infrastructure, platform, and deployment features that power AI workloads. You will collaborate with researchers, AI engineers, and infrastructure teams to ensure efficient, scalable, and reliable AI systems.

Requirements

  • 6-8 years of development experience with Python, GoLang, Java, or similar languages
  • 6+ years of experience operating highly available distributed workloads on Kubernetes following a DevOps approach
  • Experience with DevOps tooling (e.g. Helm / Ansible / Kubernetes / Prometheus / Splunk / GitLab CI)
  • Strong working experience operating distributed systems built on Linux and J2EE
  • Experience with software-defined networking, infrastructure as code, and configuration management
  • Experience building software for compliance and security in regulated environments
  • Ability to drive outcome in projects with material technical risk
  • Asset: 8+ years of experience with infrastructure and platform operations, deployments, SRE, and DevOps with a continued focus on improving Platform health

Benefits

  • health plans, including flexible spending accounts
  • 401(k) Plan with company match
  • ESPP
  • matching donations
  • flexible time away plan
  • family leave programs

Requirements Summary

6-8 years of development experience, 6+ years of experience with Kubernetes, experience with DevOps tooling, and strong working experience with distributed systems