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Location
In office (Menlo Park)
Seniority
Senior · 7+ years exp
Visa
H-1B filings in 12 months: 1
Employment
Full-Time

Confirmed on the employer's own hiring board on Nov 6, 2026. First seen by Alion on Nov 4, 2026. Meta scores B on the Alion truth index.

Overview
Company
Impact
Profile match
Meta Platforms is an American technology company founded in 2004 as Facebook and renamed in 2021 to signal its investment in immersive computing. It operates the largest family of social and messaging applications in the world, comprising Facebook, Instagram, WhatsApp, Messenger and Threads, and earns almost all of its revenue from advertising sold against that audience. Headquartered in Menlo Park, California, the company also develops the open Llama language models and the Reality Labs division behind Quest headsets and Ray-Ban smart glasses.
Meta's Traffic Efficiency team improves the performance, capacity, and reliability of the edge infrastructure connecting people to Meta's products. Edge sites face tight space, power, and hardware constraints, so efficiency directly creates usable capacity and reliability. At Meta's scale, even small efficiency gains can deliver substantial infrastructure savings while protecting product quality as demand grows.

We seek an engineering expert to set direction and lead cross-stack performance work spanning high-throughput services, operating systems and kernels, networking and NICs, CPU and memory, and server platforms. The task is to identify high-leverage opportunities, choose the right layer for each solution, and drive safe fleet-wide deployment with measurable impact on latency, throughput, resource efficiency, capacity, reliability, or total cost of ownership.

Responsibilities

Set technical direction and lead multi-team programs that improve performance, capacity, efficiency, or reliability Diagnose interactions across services, operating systems, network I/O, NICs, CPU and memory, and server platforms using profiling, tracing, telemetry, counters, and controlled experiments Prioritize the highest-leverage opportunities and implement at the right layer, contributing hands-on across layers and partnering where specialized ownership is required Build representative benchmarks and ship changes with monitoring, validation, staged rollout, rollback, and clear ownership Quantify impact and design trade-offs to influence teams outside the engineer's direct ownership Turn regressions and incidents into systemic prevention, reusable methods, and stronger team capability

Qualifications

Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience 7+ years of software-development experience, or a PhD with 4+ years of relevant experience Track record leading ambiguous, multi-team work from problem framing through large-scale production deployment, with measurable results Deep expertise in at least one area, plus significant hands-on experience in another: high-throughput services, operating systems or kernels, networking or NICs, CPU and memory, or server platforms Experience repeatedly diagnosing and improving systems across two or more of those layers Proficiency in C or C++, a scripting language, and production performance tools such as profiling, tracing, telemetry, resource attribution, or hardware counters Ability to communicate impact and trade-offs and influence teams outside direct ownership Ideal candidates combine several of these; mastery of all is not expected Linux internals, kernel networking, drivers, scheduling, packet processing, programmable networking, or NIC offloads Production-representative benchmarking, server or NIC evaluation, large-scale rollout, systems project contributions, or systemic prevention of incidents CPU, cache, memory locality, NUMA, PCIe, power, thermal, or server platform performance C++ systems optimization involving asynchronous I/O, concurrency, memory allocation, caching, transport, or overload handling High-throughput services such as CDNs, proxies, load balancers, caches, gateways, or request-processing systems

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