Scale-Up Ethernet Engineer
FuriosaAI is a South Korean AI semiconductor company building energy-efficient inference accelerators, servers, and software for enterprise and cloud AI deployments.
Funding history
Investors
About FuriosaAI
FuriosaAI develops the RNGD AI inference accelerator and NXT RNGD Server, alongside a software toolchain for compiling, optimizing, and deploying LLM and agentic-AI workloads.
Skills
Candidate Availability
Required and preferred rules are kept separate and reflect the wording in the original posting.
About the Role
You will validate Scale-Up Ethernet endpoints and switch fabrics from pre-silicon prototypes through silicon integration. You will diagnose performance bottlenecks and data-transfer failures across hardware, firmware, drivers, software, and fabrics. You will build, manage, observe, and test rack-scale systems; automate validation workflows; and evaluate AI workload performance and network interoperability.
Requirements
- Bachelor's degree in computer science, electrical engineering, or a related field, or equivalent practical experience
- Understanding of data-center Ethernet networks, switches, lossless networking, and RDMA
- Experience configuring and debugging network devices or systems in Linux
- Experience developing or debugging semiconductor system software at register and memory-map level
- Experience with rack or cluster bring-up, integration validation, and performance analysis
- Ability to automate testing, device control, and log collection using Python or Shell scripts
- Experience using AI tools and coding agents and validating their outputs with evidence
- Ability to develop hypotheses from packets, logs, and performance counters and narrow root causes through reproducible experiments
- Ability to collaborate across engineering specialties and clearly document validation methods and results
Responsibilities
- Validate Scale-Up Ethernet endpoint and SoC integration from pre-silicon prototypes through silicon
- Configure and tune NICs and switch fabrics for workload traffic characteristics
- Analyze packet captures, device counters, logs, and telemetry to isolate faults and bottlenecks
- Build clusters for collective communication and LLM inference and training workload evaluation
- Validate link stability and interoperability across MAC, PCS, FEC, SerDes, optical modules, and cables
- Design and build rack and fabric management systems
- Design rack-scale observability, failure detection, isolation, recovery, and reliability validation
- Configure and validate Scale-Up Ethernet rack systems from link bring-up through rack integration
- Automate remote console and power control, test execution, and result collection
- Orchestrate AI agents for equipment bring-up, testing, log analysis, and documentation
- Apply OCP, UEC, and SONiC Scale-Up standards and collaborate with vendors