Physical Layer Architecture Engineer
NVIDIA
Physical Layer Architecture Engineer
NVIDIA
Designs the chips and software that power AI
With the growing demand for traffic bandwidth in datacenters, efficient physical high-speed communication becomes a crucial part of the development of silicon ASC’s that serve networking infrastructures. We are looking for a PHY (Physical Layer) Architect for our Architecture team. We are positioning you to a key role to face this challenge and become part of our team, so we can continue developing the best devices in the industry.
NVIDIA's networking architecture group is seeking for a highly skilled, leading engineer to explore, and define the Physical layer of our products. As a lead engineer, you'll be responsible to define and drive features and have responsibility on the Physical layer architecture. The role will include definition of both the hardware circuitry and the firmware/software that is involved in operating the physical layer communication, with emphasis on the former. We are searching for hardworking, enthusiastic, engineer which has both highly technical skills as well as good personal skills, in order to be able to lead cross groups activities.
What you will be doing:
What we need to see:
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, sex, gender, gender expression, sexual orientation, age, marital status, veteran status, or disability status. We will ensure that individuals with disabilities are provided a reasonable accommodation to participate in the job application or interview process, to perform essential job functions, and to receive other benefits and privileges of employment. Please contact us to request an accommodation.
NVIDIA designs the chips and software that power artificial intelligence and sells complete data center systems to cloud providers, AI labs, and other businesses, along with GeForce graphics cards for gamers. Its GPUs, chips that perform thousands of calculations at once, became the main hardware for AI after researchers used them to train the AlexNet image-recognition model in 2012. NVIDIA connects many GPUs with its own processors and networking gear into servers and rack-sized computers, and developers program them through its CUDA software. These systems bring in most of its sales, and it also makes chips for cars and robots. Jensen Huang co-founded NVIDIA in 1993, and it is based in Santa Clara, California.
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