All of Meta's traffic goes over third-party Communications Service Provider (CSP) networks before it reaches Meta's users. This portion of the network which sits between Meta infrastructure and our end users has a direct impact on our users' product experience and Meta's revenue. The scope of the problem is significant since CSP networks come in a large variety of last mile access to home technologies, including fixed (fiber, cable, copper, FWA, satellite), cellular (3G/4G/5G) and in-home wireless access (WiFi 5/6/7). The market is bifurcated by a large number of infra OEMs and Service Providers on regional and country level. Many of them move slowly. Limited visibility into third-party networks and privacy/policy constraints with respect to personally identifiable information (PII) introduce unique challenges. All of this impedes scalability of solutions that require CSP collaboration and increases complexity for internal product interventions. The Communications Systems & Ecosystems team brings technical knowledge of CSP infrastructure and unique engineering skills to develop solutions that enable Meta Family of Apps (FoA) teams to improve performance, competitive advantage and efficiency over a variety of CSP network conditions, either through direct internal optimizations with prod teams (i.e., control your own destiny), or engaging with external engineering teams on CSP partner side for joint solutions (i.e., collaboration with industry).Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent practical experience. Background in communication systems and networking, with working level understanding of communication protocols across the CSP stack. Demonstrated experience in wireless networking technologies and standards (Wi-Fi and/or cellular). Experience in big data analysis - implement data swarm pipelines, analyze big datasets and automate. Demonstrated experience in evaluating and optimizing network performance with multiple skills ranging in data and signal processing, statistical methodologies, analytics, simulation, emulation, lab setups, field trials, and prototyping for feasibility and trade-off analysis. Proficiency with one or more of the following programming or scripting languages: Matlab, Python, C/C++, ns-3. MS or PhD in EE, Computer Science or Data Science with minimum 4 years of industry experience Hands-on experience with Network debugging tools (e.g. packet sniffers, protocol analyzers) Experience with developing firmware or software for production Background in Machine learning Understanding of WebRTC, QUIC, HTTP2