Senior Staff Machine Learning Engineer
ServiceNow6 hours ago
Hyderābād, IndiaStaff+
Responsibilities
- Lead the design, delivery, and production operation of complex cloud-native platform components and services.
- Serve as technical lead for major features and initiatives, translating ambiguous problems into scalable designs.
- Develop and review Kubernetes operators, controllers, infrastructure automation, and platform services using Go.
- Own Kubernetes platform capabilities across deployment, upgrades, reliability, and production operations.
- Identify and resolve technical risks related to reliability, scalability, operability, and engineering quality.
- Drive architectural design reviews, technical proposals, and cross-functional technical strategy.
- Mentor junior and mid-level engineers through code reviews, design reviews, and technical guidance.
- Build scalable, fault-tolerant ingestion and transformation workflows and operate distributed data and compute workloads.
Requirements
- 14+ years of experience designing, building, and operating large-scale distributed systems and cloud-native platforms in production.
- Demonstrated experience building and operating Kubernetes platform infrastructure at scale, including managed and self-managed Kubernetes environments.
- Hands-on experience developing Kubernetes Operators, Admission Controllers, Custom Resource Definitions, and other platform extensions using Go, Kubebuilder, Operator Framework, or similar technologies.
- Experience with EKS, AKS, GKE, and public cloud services across compute, networking, security, and identity management.
- Strong understanding of Kubernetes orchestration, scheduling, security, storage, networking, workload management, and stateful distributed workloads.
- Experience designing microservices, event-driven systems, distributed application architectures, and fault-tolerant or highly available systems.
- Experience with containers, CI/CD, GitOps, and infrastructure-as-code tools such as Terraform and Crossplane.
- Experience implementing observability and reliability practices involving metrics, logging, tracing, monitoring, alerting, and service-level objectives.
- Experience with cloud-native database platforms, large-scale data infrastructure, or stateful services on Kubernetes.
- Ability to integrate or critically assess AI-powered tooling, automated operational workflows, agentic fleet-visibility systems, and AI-driven infrastructure operations.
- Preferred experience with container networking, service mesh, mTLS, workload identity, secrets management, and distributed data or compute workload tuning.
- Preferred experience with Apache Kafka, Redis, Parquet, ORC, Avro, replication, fault tolerance, high availability, compaction, and data governance.
Benefits
- Flexible work persona with remote, flexible, or required-in-office arrangements determined by role and location.
- Regular employee position in the APAC region.
- ServiceNow provides reasonable accommodations and supports an accessible, inclusive application experience.
Categories
About ServiceNow
ServiceNow builds a cloud platform for enterprise digital workflows, covering IT service management, customer service, HR service delivery, security operations, and operations management, plus tools for custom app development. It sells subscription SaaS to large organizations and public-sector agencies to automate processes and connect data across systems. Founded in 2004 and headquartered in Santa Clara, California, ServiceNow is a public company listed on the NYSE under the ticker NOW.