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Senior C++ Software Engineer - Networking Voltron Data. We are looking for a highly motivated Senior C++ Networking Engineer, you’ll have the opportunity to work directly on Theseus, the accelerator-native data processing engine built for composability. You will work closely with Voltron Data development teams to build, optimize and maintain performant network communication systems for our distributed data analytics framework. You will add new features, make it run faster and more scalable and even contribute to new core architectural components that will enable the engine to run at Petabyte scale.. Why work at Voltron Data?. We are Going for Impact. : We are a Series A, venture-backed startup assembling a global team to design next-generation data systems, creating a new foundation for data processing built on composable open standards, with Theseus, our GPU query engine for petabyte-scale ETL, harnessing the speed and efficiency of modern hardware.. We are Committed to Bridging Open Source Communities:. We are a collection of open source maintainers who have been driving open source ecosystems over the last 15 years, particularly in the C++, Python, and R programming ecosystems. . We are Building a Diverse, Inclusive Company: . We are creating a representative, equitable, and respectful workplace that prioritizes employee growth. Everyone at Voltron Data is bought into the company’s success; all voices are critical to shaping the organization’s future. . Upon Joining:. Spending time learning about the Apache Arrow columnar memory layout, streaming binary format, random access binary format, and other serialization mechanisms.. Diving into the data processing engine architecture, how all the different components interact with each other and how data flows through the compute graph. . Understanding how existing data communication systems work.. Learning and embracing the software development culture at Voltron Data.. Within a month:. Implementing new high performance networking and communication primitives. Optimizing performance of existing networking and communication primitives. Participating in peer code review in networking and communication functionality development . Contributing to technical discussions and technical design documents. Within 6 months:. Developing a comprehensive set of low level benchmarks for networking and communication primitives targeting various implementations like intra-process shared memory, inter-process shared memory, Infiniband, RoCE, TCP/IP, and others to enable tracking and addressing performance regressions. Identifying and building reusable components across different networking and communication primitives to ensure a high quality and maintainable codebase. Within 12 months:. Analyzing communication throughput in a massively parallel and distributed query engine, to identify inefficiencies and designing solutions to solve those inefficiencies. Continuing to build out the collection of networking and communication primitives to ensure they are as high quality as possible, balancing performance, usability, and maintainability. Previous experience that could be helpful:. Experience with networking software libraries like MPI, UCX, libfabric, DPDK, Seastar, and/or others is a plus. Experience with Infiniband, RoCE, TCP/IP and other networking technologies. Understanding of large scale distributed data processing systems is a plus. Understanding of unix network programming, libibverbs, RDMA, and/or others. Building libraries and/or applications that leverage asynchronous execution, threading, coroutines, futures, or other techniques to handle concurrency.  . US Compensation - . The salary range for this role is between $150,000-$220,000. We have a global market-based pay structure which varies by location. Please note that the base pay range is a guideline and for candidates who receive an offer, the exact base pay will vary based on factors such as actual work location, skills and experience of the candidate. This position is also eligible for additional incentives such as equity awards.