Senior Staff Machine Learning Engineer

Technical lead role building and operating cloud-native platform components and AI-powered operations at ServiceNow Hyderabad.

• 1Lead the design and delivery of complex components and services within the cloud-native platform, owning them from design through production operation
• 2Act as the technical lead for major features and initiatives within the team, translating ambiguous problems into clear, scalable, and executable designs
• 3Partner with Principal and Distinguished Engineers to ensure alignment with broader platform architecture, engineering standards, and long-term technical strategy
• 4Identify technical risks early and drive them to resolution, with a strong focus on reliability, scalability, operability, and engineering excellence
• 5Maintain a strong hands-on presence across the development lifecycle, including designing, coding, and reviewing core systems such as Kubernetes operators, controllers, infrastructure automation, and platform services
• 6Mentor mid-level and junior engineers while raising the engineering bar through code reviews, design reviews, technical guidance, and collaborative problem-solving

• Experience leveraging or critically thinking about how to integrate AI into engineering and platform work—AI-powered tooling, automated operational workflows, agentic systems for fleet visibility and operations, or reasoning about AI’s impact on how infrastructure is built and run
• 14+ years of experience designing, building, and operating large-scale distributed systems and cloud-native platforms in production environments
• Demonstrated experience building and operating Kubernetes platform infrastructure at scale, with ownership of platform capabilities through deployment, upgrades, and production operations
• Hands-on developing Kubernetes Operators, Admission Controllers, or other platform extensions using Kubebuilder, Operator Framework, or similar technologies
• Experience operating both managed Kubernetes services (EKS, AKS, GKE) and self-managed Kubernetes environments
• Experience supporting cloud-native database platforms, large-scale data infrastructure, or stateful services on Kubernetes
• Strong software engineering expertise in Go, with hands-on experience developing Kubernetes Operators, Controllers, Custom Resource Definitions (CRDs), and platform automation capabilities
• Deep understanding of Kubernetes architecture, including orchestration, scheduling, security, storage, networking, and workload management