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You will be responsible for developing, executing, and maintaining tests for collective communication operations (AllReduce, AllGather, ReduceScatter, AllToAll) on custom networking silicon — validating that the ASIC correctly enables large-scale distributed AI training workloads.
You will be responsible for developing, executing, and maintaining tests for collective communication operations (AllReduce, AllGather, ReduceScatter, AllToAll) on custom networking silicon — validating that the ASIC correctly enables large-scale distributed AI training workloads.
Language
Proficiency
Usage
C/C++
Expert (Must-have)
Writing test frameworks, RDMA verbs test suites, driver-level test development, loopback and traffic tests
Python
Strong (Must-have)
Test automation, CI/CD integration, orchestration of multi-node test scenarios, emulation test infrastructure
Bash/Shell Scripting
Proficient (Good-to-have)
Test execution scripts, environment setup, multi-host coordination
Develop test suites for collective operations (AllReduce, AllGather, ReduceScatter, AllToAll) targeting Trantor ASIC across emulation, FPGA, and silicon platforms
Write RDMA verbs-level tests using the RoCE Verbs Testing Framework (rdma-core Verbs API) — covering positive, negative, and error-injection scenarios
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Validate multi-node, multi-NIC collective communication patterns, ensuring correct behavior under various topologies (rail-aligned, cross-rail, multiplanar)
Develop traffic generation and validation tools for RDMA collectives at scale — covering data integrity, performance, and error handling
Integrate tests into CI/CD pipelines for regression prevention on every code change and nightly builds
Collaborate with driver, firmware, architecture, and modeling teams to define test plans and ensure complete coverage of networking features
Run and analyze performance benchmarks (NCCL-tests, perftest, rdma_gen) to identify regressions and validate throughput/latency targets
Debug and root-cause failures across the full stack — ASIC RTL, firmware, driver, rdma-core provider, and user-space collectives
InfiniBand / IB Verbs API — Experience with libibverbs, rdma-core, ibv APIs
Network Topologies for AI Training — Rail-optimized fabrics, fat-tree, multi-planar designs, PXN
Traffic Congestion & Flow Control — PFC (Priority Flow Control), ECN, congestion management for lossless fabrics
DMA & Memory Subsystems — GDR (GPUDirect RDMA), host memory registration, IOMMU
Protocol Conformance Testing — ANVL or similar automated conformance testing methodologies
Background in silicon validation for networking chips (switches, NICs, DPUs)
Experience with pre-silicon validation environments (emulation, FPGA prototyping, software models/QEMU)
Familiarity with infrastructure or large-scale hyperscaler networking
Contributions to open-source RDMA/networking projects (rdma-core, Linux kernel networking, NCCL)
Understanding of AI/ML training workloads and how network performance impacts training efficiency
Experience with build systems and test infrastructure at scale
B.S./M.S. in Computer Science, Electrical Engineering, Computer Engineering, or related field
Advanced degree preferred but not required with equivalent industry experience
HCL Technologies is a global IT services and consulting company offering digital, engineering, cloud, and AI solutions. Headquartered in Noida, India, it serves clients across industries in over 60 countries.
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