ServiceNow
Senior (DevOps) Machine Learning Engineer - Federal
- Location
- Santa Clara, CALIFORNIA, United States
- Work model
- OnSite
- Seniority
- Senior
- Employment
- FullTime
- Posted
- Added to Codestelle
Language requirements
- German
- Not specified
- English alone
- Not specified
Based on explicit wording in the listing. “Not specified” does not mean a language is optional.
About this role
What you get to do in this role:
The Advanced Technology Group (ATG) 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.
You will play a major part in building AI and Machine Learning (ML) solutions that transform the user experience and workflow efficiency of enterprise services. Traditional analytical tools tend to require a technically knowledgeable user to produce even simple results. We are taking a completely fresh approach with the expectation that any user, regardless of technical knowledge, can use the AI/ML solutions we develop to operate the services in the enterprise setting in a thoughtful and scalable manner. We are just getting started with our early-adopter customers and we need your help in building and making available an amazing range of solutions to our 5k+ enterprise customers around the world.
- Build the best cloud-based AI/ML solutions to power intelligent enterprise services
- Collaborate daily with a team of like-minded developers, product managers and quality engineers to produce quality software
- Work with product owners to understand detailed requirements and own your code from design, implementation, testing and delivery of high-quality solutions to our users
To be successful in this role you have:
- Expertise in Go or Python, 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 requirements
- 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
Desired skills but not required:
- 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.
For positions in this location, we offer a base pay of $161,300 - $274,200, 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.