Runware
Information Technology and Services
PlatformDataAnalyst
Neural analysis suggests this role is
optimal for Mid+ candidates.
“Platform Data Analyst at Runware. Skills: Platform Observability, Usage Analytics, Performance Monitoring. Build inference time tracking. Monitor implementation changes”
What You'll Achieve.
full visibility; understand, measure, and optimize; informed decisions; continuously improve performance and reliability; scale smoothly; make it better
Industry & Context.
digging into the data; flagging problems
existing right to work in the UK
What They're Looking For.
Must Have
data analytics, observability, monitoring, metrics/logging/tracing frameworks, backend systems, distributed architectures, raw metrics into actionable insights, dashboards for internal and external stakeholders, AI model monitoring
Nice to Have
AI/ML infrastructure, inference pipelines, GPUs, Python APIs, FastAPI, Node environments, high-throughput real-time systems, Startup or scale-up experience
What You'll Do.
Build inference time tracking
Monitor implementation changes
Provide automated alerts
Build internal dashboards
Provide client-facing dashboards
Work with DevOps & backend
Provide infra insights
Select and maintain tooling
Ensure data pipelines reliable
Build simple dashboards
How You'll Work.
Team & Collaboration
work with ML, backend, DevOps, and product teams
Full Job Description
### **About Runware** Runware is building a high-performance, full-stack AI media-creation platform — empowering developers and companies to generate any type of media instantly. As we scale fast and integrate increasingly complex models, we need stronger visibility, analytics, and monitoring across the whole platform stack. We’re looking for a **Data Expert** (Analytics + Monitoring + Observability) to help us better understand, measure, and optimize how the Runware platform performs at scale — internally and for our clients. ### **🎯 Mission** Your main goal is to give Runware **full visibility** over: * End-to-end inference performance * Integration usage and model activity * Errors, delays, bottlenecks, regressions * Internal and client-facing analytics dashboards * Health and performance of production pipelines You will provide the data insights that allow engineering, ML, backend, DevOps, and leadership to make informed decisions — and to continuously improve performance and reliability. ### **🧩 What You Will Do** ### **Performance Monitoring & Benchmarking** * Build and maintain E2E **inference time tracking** (global and per-model). * Monitor how implementation changes impact total request latency. * Detect regressions introduced by suboptimal code paths. * Provide automated alerts & historical trends. ### **Usage & Analytics Reporting** * Build dashboards for internal use (engineering, product, leadership). * Provide **client-facing usage dashboards** (requests, errors, success rate, performance). * Support clients who need visibility to debug their integrations. * Track model-level usage, API endpoints usage, adoption metrics, etc. ### **Platform Observability** * Implement metrics, logs, and traces that help the entire platform scale smoothly. * Work closely with DevOps & backend teams to improve system observability. * Provide insights that guide infra decisions (GPU allocation, autoscaling, caching, batching, etc.). ### **Data Infrastructure Ownership*
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