About Us

At Cloudflare, we are on a mission to help build a better Internet. Today the company runs one of the world’s largest networks that powers millions of websites and other Internet properties for customers ranging from individual bloggers to SMBs to Fortune 500 companies. Cloudflare protects and accelerates any Internet application online without adding hardware, installing software, or changing a line of code. Internet properties powered by Cloudflare all have web traffic routed through its intelligent global network, which gets smarter with every request. As a result, they see significant improvement in performance and a decrease in spam and other attacks. Cloudflare was named to Entrepreneur Magazine’s Top Company Cultures list and ranked among the World’s Most Innovative Companies by Fast Company.

At Cloudflare, we’re not looking for people who wait for a polished roadmap; we’re looking for the builders who see the cracks in the Internet that everyone else has simply learned to live with. We value candidates who have the instinct to spot a "normalized" problem and the AI-native curiosity to create a solution using the latest tools. Our culture is built on iteration, leveraging AI to ship faster today to make it better tomorrow, while ensuring that every improvement, no matter how small, is shared across the team to lift everyone up. If you’re the type of person who values curiosity over bureaucracy, and that AI is a partner in solving tough problems to keep the Internet moving forward, you’ll fit right in.

Available Locations

New York, NY

Washington, DC

San Francisco, CA

About the Role

Cloudflare’s architecture is built on a homogeneous edge: every server in over 330 cities runs every service—from L4/L7 proxies (FL2, Pingora) and DNS to the Workers runtime, cache, and storage. While this design maximizes hardware utilization, it creates a difficult distributed attribution problem. Machine-level telemetry tells us how loaded a server is, but not which product, customer, or upstream service is responsible for that load.

MAPS (Metrics and Analytics for Product Segmentation) is a newly formed team building the core instrumentation, collection, and data platform to solve this from the ground up. We are architecting a system to continuously measure CPU, network bandwidth, memory, and storage utilization across the entire global fleet without sampling—attributing resource consumption both to the underlying system service and to the specific product, account, and zone being served.

The data MAPS produces serves two critical functions at Cloudflare:

Real-Time Control Plane: MAPS is the primary telemetry input for Cloudflare’s next-generation global load balancer, shifting traffic management from open-loop heuristics to closed-loop routing driven by real-time, per-service resource capacity and consumption (within seconds).
Fleet Economics & Capacity Planning: MAPS provides the long-term analytical dataset in ClickHouse used to map product demand forecasts to physical hardware requirements, calculate true cost-to-serve per product, and drive multi-year infrastructure investments.

What You’ll Do

You will work across the full lifecycle of a greenfield, high-throughput telemetry system running on every machine at the Cloudflare edge:

Host-Level Instrumentation ("Outside View"): Build and maintain low-overhead Linux daemons (netacctd, maps_collector) in Rust and C that use eBPF (cgroup_skb) and cgroup v2 accounting to measure per-service resource consumption directly from the kernel.
High-Performance Client Libraries ("Inside View"): Architect non-blocking, zero-allocation reporting SDKs in Rust and Go used by Cloudflare’s highest-throughput data-plane services to report per-request resource usage and product attribution over local Unix domain sockets.
Edge Aggregation & Streaming: Build the per-machine collector daemon that ingests millions of events per second, performs bounded in-memory time-window aggregation, serves low-latency gRPC streams to the global load balancer, and flushes batch rollups to ClickHouse.