Senior ; DevOps) Machine Learning Engineer

Position: Senior Staff (DevOps) Machine Learning Engineer
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, Service Now is the AI control tower for business reinvention.

Our Service Now 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 About the team - The AI Services Platform Group at Service Now 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 (Dev Ops) 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  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. Qualifications 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 Git Hub 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…