Full-Time
Network and Server Performance Test Engineer
Confirmed live in the last 24 hours
Cerebras
201-500 employees
Develops AI acceleration hardware and software
Mid, Senior
Sunnyvale, CA, USA
- Four to eight years of experience in Software Development, Quality Assurance, System Test of Switches and Routers at a Networking equipment vendor.
- Bachelor’s degree or higher in Electrical Engineering, Computer Engineering, Computer Science, or related majors with focus on Networking or Computer System Architecture.
- Understanding of RDMA congestion control mechanisms on InfiniBand and RoCE Networks.
- Must have deep understanding of networking protocols TCP/IP, BGP, PFC, ECN, QoS, MLAG, ECMP, and VRF.
- Experience with computer system architecture, especially on CPU SoC or Platform Architecture, Interconnect Fabric, and Memory sub-system.
- Experience designing and implementing large switching and routing networks.
- Expertise in Linux tools such as lspci, ping, traceroute, tcpdump, ifconfig, ip link, ip route, arp, /proc/net, /proc/sys/net, vmstat, netstat, ttcp, iperf, strac, memtest, fio, ozone, and iometer.
- Strong technical abilities, problem-solving, design, coding, and debugging skills.
- Must be proficient in python. Strong python coding experience is a must.
- Proficient in Networking Test Tools like IXIA and Spirent SmartBits.
- Manage and optimize end to end network performance of complex AI infrastructure including Servers and Switches.
- Evaluate and recommend Servers, Switches and Router for next generation infrastructure, with focus on performance and cost improvement.
- Identify experiments, tools, and methodology to test networking equipment for network performance and network traffic engineering.
- Design and setup test beds to exercise and evaluate vendor equipment from Arista, Juniper, Cisco, Dell, HPE.
- Work with architects, software engineers to create test cases, write test scripts, execute tests, and document results of evaluation of solution from different vendors.
- Recommend most optimize configurations to AI infrastructure deployment teams.
- Troubleshoot, isolate, and drive issues to resolution through partnerships with other teams and server/network equipment vendors.
- Provide solutions for efficient networking design for AI infrastructure.
Cerebras Systems specializes in accelerating artificial intelligence (AI) processes with its CS-2 system, which is designed to replace traditional clusters of graphics processing units (GPUs) used in AI computations. The CS-2 system simplifies AI tasks by eliminating the need for complex parallel programming and cluster management, making the process more efficient. Cerebras serves a variety of clients, including major pharmaceutical companies and government research labs, providing them with faster results for critical applications like drug response predictions. The company operates in the high-performance computing and AI markets, generating revenue through the sale of its proprietary hardware and software solutions, including the CS-2 system and associated cloud services. Cerebras aims to reduce the overall cost of AI research and development while enabling clients to achieve quicker results and lower latency in AI inference.
Company Stage
N/A
Total Funding
$700.4M
Headquarters
Sunnyvale, California
Founded
2016
6 month growth
↑ 8%1 year growth
↑ 16%2 year growth
↓ -3%
Simplify's Take
What believers are saying
- Cerebras' IPO and significant funding, including $720 million raised, position it for substantial growth and market penetration.
- Collaborations with industry giants and government labs, such as GlaxoSmithKline, AstraZeneca, and Argonne National Lab, validate the effectiveness and demand for Cerebras' technology.
- The CS-2 system's ability to produce faster results in critical applications like cancer drug response prediction models highlights its transformative potential in healthcare and scientific research.
What critics are saying
- Competing against established giants like Nvidia poses significant market challenges and could impact Cerebras' market share.
- The high cost and complexity of developing and maintaining cutting-edge hardware like the WSE-3 chip could strain resources and affect profitability.
What makes Cerebras unique
- Cerebras' CS-2 system replaces traditional GPU clusters, eliminating complexities in parallel programming and distributed training.
- The WSE-3 chip, with 40 trillion transistors, is designed to train AI models 10 times larger than current top models like GPT-4, setting a new industry standard.
- Strategic partnerships with major entities like Dell and Aleph Alpha enhance Cerebras' reach and influence in the AI and high-performance computing markets.
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