דרושים Software Qa Engineer Intern - Compute ב-אנבידיה ב-China, Shenzhen

NVIDIA is looking for talented and creative Thermal Engineering student
What you'll be doing:

• Product thermal design and thermal/mechanical definition for next generation products.

• Manage the development, specifications, design and manufacturing for your thermal solutions, i.e. heat sinks, interface materials, structures, fan, acoustics, thermally related ergonomics, enclosures, etc.

• Prepare early design concepts and drive product thermally related design trade-offs

• Research new materials, processes, and technologies to meet product goals

• Support manufactory side thermal related issues debug and drive for solution.

• Work with global team from concept design to manufacture and quality issue.

What we need to see:

• Must be pursuing a MS in thermal and Mechanical Engineering

• Exposure and proficiency with at least one heat transfer and thermal engineering analysis SW tool (e.g. IcePak, FloTHERM, Fluent)

• Strong communication skills in English

Ways to stand out from the crowd:

• Major in Thermodynamics and/or Heat Transfer

• Knowledge of Design for Manufacturing (DFM) principles and techniques

• Intermediate knowledge Level on MS Word, PowerPoint, Excel

• Academic knowledge: Statistics, Mechanics of Materials

• Fluent in English

What you'll be doing:

• Drive board/system level signal and power integrity requirements

• Lead board/system SI/PI design activities, including PCB stackup/material selection, design guide implementation, layout review, and post-layout analysis

• Work closely with Architecture, ASIC, Mixed Signal, Package, and PCB Design teams to design and ensure system SI/PI performance meets expectation before Gerber out, also work closely with Design Validation teams to support SI/PI failure analysis

• Develop novel algorithms & new methodologies to improve SI/PI modeling efforts

• Work with Application Engineering teams to support customers w/ SI/PI questions

• VNA & TDR measurements to support model correlation efforts and improve confidence in design stage

What we need to see:

• MS/BS in EE or equivalent experience

• Minimum 5+ years of experience as a SI/PI engineer

• Deep understanding of electromagnetics, specifically electromagnetic waves including transmission line theory and via properties

• Proficient with HFSS, Sigrity, Hspice, and/or other simulation tools

• Experienced with Cadence Allegro PCB designer and Constraints Manager

• Understanding of high volume manufacturing variations and impact to channel signal integrity

• Exposure to lab measurements including VNA & TDR experience

• Passionate about SI/PI work

• Good written & verbal interpersonal skills in English

Ways to stand out from the crowd:

• Familiarity with NRZ/PAM-4/Duo-binary signaling schemes

• Exposure to interface timing budgets and system modeling

• Familiarity with high-speed I/O design concepts including clock generation, transmitter & receiver design, and equalization schemes

• PDN analyses including model generation and time domain simulation

• Experience w/ Matlab, Python, and C as well as exposure to package design

You need to work independently and be highly self-motivated. You should drive issues with little or no supervision. A key success for this position is not only a thorough understanding of NVIDIA DRIVE platform hardware and software stack, but also a solid grasp of customer system and data pipeline design, and various requirements. Excellent communication skills, flexible in task assignments and working under pressure are also indispensable.

What you'll be doing:

• You will have good opportunity to work on the leading-edge technology of autonomous driving.

• Closely communicate and work with NVIDIA DRIVE customers, find out how to technically satisfy customer requirements.

• Software development on NVIDIA DRIVE SDKs, deep knowledge on the SDK functionalities and performance. deeply understand various vehicle sensors including Camera, Lidar, Radar, GPS and so on.

• To support customers more efficiently, you will work with internal global teams to align customer's requirements and SDK development status.

• Master's degree or higher in Computer Science, Software Engineering, or a related field.

• 3+ years of embedded, robotic, or automotive software development work experience.

• Excellent C and C++ skills.

• Experience in at least of the following technical domain: camera capture, ISP processing, image 2D, rendering, display, encoding .

• Good English language skills to work effectively with global development and support team.

• Know about modern autonomous driving operation system scheduling policy, threading, synchronization, and parallel computing to build highly scalable and stable applications.

• Self managing and ability to break down complex problems in to manageable tasks

• Experience in developing system software mostly in user space but also feel comfortable in digging into kernel space and low-level drivers.

What you’ll be doing:
build/maintain/fine-tunequantitatively analyzing models to conduct data mining for Predictive NPI to improve the performance of mass production proactively, which includes:

• Participate in SW tool development for monitoring the status of mass production, managing bonepile, accelerating failure analysis and raising risk alert

• Design data visualization for regular reports

• Develop and maintain correlate SW tools and database at an as-needed basis.

• Collaborating with Info Security team for tools deployment at factories.

What we need to see:

• Bachelor or Master of CS/EE/Math, or equivalent experience.

• 5+ years working experience.

• Well understand data analytics principles and network security.

• Master SQL, familiar with using Python to do data cleaning & analyzing.

• Profound experience on data visualization and Mysql database usage.

• Master HTML and CSS (Bootstrap), Javascript and jquery programming.

• Very good at OOP programming of PHP.

• Able to quickly understand the business and discover the connections between business & data.

• Experience in Python

• Proficient English.

Ways to stand out from the crowd:

• Have both hardware and software background especially in factory environments.

• Machine Learning/Deep Learning training and/or experience with Pytorch/Tensorflow is preferred

• Well know the principle of Shift Left.

What you will be doing:

• Design responsibility for the creation of new products designed around our GPUs, DPUs and CPUs to cover Graphics, Self-driving platform, Server, and Data center.

• The LDE drives every aspect of design execution, initial test and bring-up, manages documentation required to release the product to manufacturing and partners, and is the main interface to theSilicon/Thermal/Mechanical/SI/EMCengineers.

• The scope of the LDE role has been carefully tailored to allow these individuals to consistently deliver world class product quality on a SOL schedule, while applying great attention to detail and quality of execution.

• Research the new feature/circuits and involve theestablishment/discussionof industry standards, then implement them on the next generation product/platform design.

What we need to see:

• You will be completing your bachelor’s or master’s degree in Electrical Engineering or Computer Science or Computer Engineering

• Knowledgeable in high-speed signal design rules and basic power design methodologies

• Proficiency in digital/analog circuit simulation and fault diagnosis.

• You have exposure or internship experience with design tools (Multisim or equivalent simulation tools, design tools like Cadence, Concept, OrCAD).

• Your work displays your passion for circuit development and strong problem-solving skills

• Strong communication and interpersonal skills are required

Ways to stand out from the crowd:

• Prior hardware design experience related to high-speed subsystem design or DC-DC power module design is a huge plus.

• Familiarity with Graphic card or Autonomous driving subsystem industrial standard such as PCI Express protocols, memory management, automotive design rules, high-speed IO protocols and/or on-chip interconnect.

NVIDIA is seeking a Senior High Performance Computing (HPC) and AI Networking Performance Research and Analysis Engineer to join our Performance group. In this exciting role, you will profile and analyze AI workloads on large GPUs and CPUs scale clusters for distributed Deep Learning LLM training focused on collectives communication and networking. You will interact with many types of hardware and platforms, such as HCAs, Switches, CPUs, GPUs, and Systems. You will develop performance analysis tools and methodologies to dive deeply into the details and understand performance expectations, limitations, and bottlenecks.

What you'll be doing:

• Exploring and researching AI workloads and DL models specifically tailored for large-scale deep learning LLM training on NVIDIA supercomputers and distributed systems focusing on high-performance networking and Nvidia Collective Communications Library (NCCL).

• Benchmarking, Profiling, and Analyzing the performance to find bottlenecks and identify areas of improvement and optimizations, with a strong emphasis on networking aspects.

• Implementing performance analysis tools.

• Collaborating with many teams from hardware to software to provide performance analysis insights.

• Defining performance test planning , setting performance expectations for new technologies and solutions, and working to reach the performance targets limits.

What we need to see:

• B.Sc in Computer Science or Software Engineering or equivalent experience

• 5+ years of experience with high-performance Networking (RDMA, MPI, NCCL, Congestion Control Algorithms)

• Demonstrated Performance Analysis skills and methodologies.

• Experience with NVIDIA GPUs, CUDA library, deep learning frameworks like TensorFlow or PyTorch, combined with expertise in networking collective communication libraries (such as NCCL) and protocols (such as RoCE and RDMA).

• Fast and self-learning capabilities with strong analytical and problem-solving skills.

• Programming Languages: Python, Bash and C languages

• Experience with Linux OS distros.

• Great teammate with good communication and interpersonal skills

Ways to stand out from the crowd:

• In-depth knowledge and experience with AI workloads and benchmarking for distributed LLM training.

• Knowledge in CUDA, and NCCL libraries.

• Knowledge in Congestion Control algorithms.

• In-depth System knowledge and understanding (Intel / AMD / ARM CPUs, NVIDIA GPUs, HCA, Memory, PCI).

• Strong Performance Analysis skills and methodologies using modern tools.

What you'll be doing:

• Process PCB Library requests for new parts and analyze/modify existing library parts per DFM/design consideration.

• Works closely with Design Engineers, Mechanical Engineers, Component Engineers, and Process Engineers to build PCB component footprints. Develop and maintain mechanical component and electrical component libraries by taking assembly, reliability and DFM points into account.

• Maintain and optimize the PCB library management process. Understand and implement to current IPC standards, and DFM guidelines, while supplying to improve our current PCB/ECAD/MCAD library process/rules.

• New PCB/PCBA technology/process study and reasonability estimation.

What we need to see:

• Demonstrated ability working on PCB library symbol creation.

• Proficient in using Cadence/Allegro for symbol creation.

• Skilled in using AutoCAD.

• Bachelor degree or equivalent experience in Electrical or Mechanical Engineering, Master degree is preferred.

• Excellent analysis skills and ability to resolve the complicated issues.

• Knowledge of PCB manufacturing processes and board assembly soldering processes in detail.

• 3 years above of PCB Layout experience

Ways to stay out from the crowd:

• Familiarity with IPC-7351 for library component creation.

• Experience in mechanical design.

• Knowledge of dimension and position tolerance and analysis.

• Background with PTC’s CREO and WindChill.

• Familiarity with Valor usage and the structure.