ServiceNow
Staff Engineer, Machine Learning Systems & Reliability - Moveworks
Mountain View, CALIFORNIA, United States · Staff · Full-time · Posted Sep 10, 2026
- Experience
- Typically 7+ years in software engineering, platform engineering, SRE, production engineering, or ML infrastructure.
- Visa sponsorship
- For positions requiring access to controlled technology subject to export control regulations, employment is contingent upon obtaining any export license or other approval required by relevant authorities.
About the job
Build and operate reliable production systems for machine-learning models, agentic workflows, and self-learning capabilities, from experimentation through deployment and ongoing improvement.
What you'll do
- Create ML lifecycle platforms and continuous-delivery workflows with automated quality, safety, performance, and compatibility checks.
- Establish controlled feedback loops, safe rollout mechanisms, and SRE practices including SLIs, SLOs, monitoring, and incident response.
- Improve the scalability, availability, latency, and cost efficiency of ML workloads while providing technical leadership across teams.
What they ask for
- Strong software-engineering skills in Python and at least one of Go, Java, C++, or Rust.
- Experience designing, operating, and troubleshooting distributed production systems.
- Hands-on experience with cloud infrastructure, containers and Kubernetes, infrastructure as code, CI/CD, and modern observability.
- Practical understanding of the ML lifecycle and familiarity with SRE practices such as SLIs/SLOs, error budgets, incident management, and blameless postmortems.
Tools
Python, Go, Java, C++, Rust, Kubernetes, LLMs
AI focus
Productionize machine-learning models, agentic workflows, and self-learning approaches; apply LLMs or agentic automation to evaluation, troubleshooting, and operational workflows.
Model-written summary · the original posting is authoritative