Supercomputing Engineer; Network

About Etched

Etched is building the world’s first AI inference system purpose-built for transformers - delivering over 10x higher performance and dramatically lower cost and latency than a B200. With Etched ASICs, you can build products that would be impossible with GPUs, like real-time video generation models and extremely deep & parallel chain-of-thought reasoning agents. Backed by hundreds of millions from top-tier investors and staffed by leading engineers, Etched is redefining the infrastructure layer for the fastest growing industry in history.

We are seeking highly motivated and skilled Supercomputing Engineers (Network) to join our team. This team plays a critical role in developing, qualifying, and optimizing high-performance networking solutions for large-scale inference workloads. As a Pod Software Engineer, you will focus on developing and qualifying software that drives communication amongst Sohu inference nodes in multi-rack inference clusters. You will collaborate closely with kernel, platform, and telemetry teams to push the boundaries of peer-to-peer RDMA efficiency.

• High Performance Peer to Peer Networking: Design, develop, and implement RDMA based networking peering, supporting high bandwidth, low latency communication across PCIe nodes within and across racks. Includes work across Operating System, kernel drivers, embedded software and system software.

• Test Development: Develop tests that qualify host processors (x86), NICs, TORs and device network interfaces for high performance.

• Burn-in integration: Furnish burn-in teams with tests that represent both real-world use cases and workloads for device to device networking, and extreme-load stress testing.

• Performance/Health Telemetry Design: Define the key metrics that system software must collect to maintain high availability and performance under extreme communications workloads.

• Analyze performance deviations, optimize network stack configurations, and propose kernel tuning parameters for low-latency, high-bandwidth inference workloads.

• Design and execute automated qualification tests for RDMA NICs and interconnects across various server configurations.

• Identify and root-cause firmware, driver, and hardware issues that impact RDMA performance and reliability.

• Collaborate with ODMs and silicon vendors to validate new RDMA features and enhancements.

• Implement and validate peer RDMA support for GPU-to-GPU and accelerator-to-accelerator communication.

• Modify kernel drivers and user-space libraries to optimize direct memory access between inference pods.

• Profile and benchmark inter-node RDMA latency and bandwidth to improve inference job scaling.

• Optimize NIC and switch configurations to balance throughput, congestion control, and reliability.

• Proficiency in C/C++

• Proficiency in at least one scripting language (e.g., Python, Bash, Go).

• Strong experience with device-to-device networking technologies (RDMA, GPUDirect, etc.), including RoCE.

• Experience with zero-copy networking, RDMA verbs and memory registration.

• Familiarity with queue pairs, completions queues, and transport types.

• Strong understanding of operating systems (Linux preferred) and server hardware architectures.

• Ability to analyze complex technical problems and provide effective solutions.

• Excellent communication and collaboration skills.

• Ability to work independently and as part of a team.

• Experience with version control systems (e.g., Git).

• Experience with reading and interpreting hardware logs.

• Experience with networking technologies like NVLink, Infiniband, ML Pod interconnects.

• Experience with widely deployed Top of Rack Switches (Cisco, Juniper, Arista, etc.)

• Knowledge of server virtualization.

• Experience with tracing tools like perf, eBPF, ftrace, etc.

• Experience with performance testing and benchmarking tools (gProf, vTune, Wireshark, etc.).

• Familiarity with hardware diagnostic tools and techniques

• Experience with containerization technologies (e.g., Docker, Kubernetes).

• Experience with CI/CD pipelines.

• Experience with Rust.

• Candidates who have worked on…