Senior Machine Learning Engineer (DevOps, Federal)

• 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
• 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

Benefits

• Generous family leave
• Matched donations
• Annual learning stipends
• Flexible PTO
• Competitive retirement plan
• Paid volunteer time- Experience building new products that use challenging algorithms
• Knowledge of unit testing, profiling, and code tuning
• Expertise in coding efficient, object-oriented, modularized and quality software
• Expertise in Go or Python, Design Patterns, time and space-efficient algorithms
• Knowledge of core AI/ML techniques and algorithms
• 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