About ServiceNow
It all started when engineer Fred Luddy wrote code that automated a tedious task for his coworker, Phyllis. She cried tears of joy. Backed by Greylock and Sequoia.
About the role
Join the Compute Engineering organization, which builds the scheduling, capacity, and performance systems that run our platform across private and public cloud. Found on 1752vc Careers, the job board for startup and VC roles.
What they're looking for
- 12+ years of related experience in software engineering, cloud, or infrastructure automation with a Bachelor's degree, or 8+ years and a Master's degree, or a PhD with 5+ years of experience, or equivalent experience
- Deep experience designing multi-tenant, cloud-native SaaS at enterprise scale, including distributed systems, large-scale data systems, APIs, and microservices
- Experience designing or operating large-scale schedulers or resource managers, such as Kubernetes, Slurm, or internal equivalents
- Strong programming skills in Go, Python, or Java, with experience in related languages
- Experience with capacity planning, performance engineering, or load testing at scale
- Hands-on experience applying ML in production, including models, feature pipelines, or ML platforms. Using AI tools alone is not enough
More about this role
We are hiring across multiple engineering levels. Final level alignment is determined by experience, technical expertise, demonstrated impact, and interview performance.
Join the Compute Engineering organization, which builds the scheduling, capacity, and performance systems that run our platform across private and public cloud.
- Design and evolve the compute scheduler and resource-management systems, including placement, prioritization, preemption, and fairness across workloads.
- Build capacity models and forecasts across private and public cloud, and turn them into reservation and placement decisions.
- Establish performance and scale testing: benchmarks, load tests, regression detection, and SLOs for scheduling latency and throughput.
- Apply AI and ML to forecasting, anomaly detection, and placement optimization where they outperform simpler approaches.
- Write and maintain declarative, software-defined infrastructure at scale, with build systems, web services, and automation that are specified, documented, and testable.
- Research and adopt open-source and commercial tools and methods that improve compute efficiency and reliability.
- Partner with networking, orchestration,...
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