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At NVIDIA, we're driven by a profound commitment to transforming the future of computing, artificial intelligence, and visualization technologies. Joining NVIDIA's AI Efficiency Team means contributing to the infrastructure that powers our innovative AI research. This team focuses on optimizing efficiency and resiliency of ML workloads, as well as developing scalable AI infrastructure tools and services. Our objective is to deliver a stable, scalable environment for NVIDIA's AI researchers, providing them with the necessary resources and scale to foster innovation.
We are seeking a senior network software engineer to join our team. As a Senior Network Software Engineer, you will be instrumental in co-designing and implementing innovative solutions that power AI applications at an unprecedented scale. Your expertise in network software architecture and high-performance interconnects will drive innovation and enable us to deliver platforms that redefine what is possible. This is an exceptional opportunity to push the boundaries of technology and shape the future of AI and work with a world-class team of like-minded engineers.
What you will be doing:
Collaborate with multi-functional teams to analyze, co-design, and develop networking software and hardware for innovative AI platforms.
Drive the development of new networking algorithms and protocols for point-to-point and collective operations at scale.
Identify bottlenecks and inefficiencies in application code, proposing optimizations to enhance performance and network utilization.
Design and implement performance benchmarks and testing methodologies to evaluate performance at scale.
Provide guidance and recommendations for optimizing AI applications for speed, scalability, and resource efficiency.
Share knowledge with domain expert teams as they develop applications for the next generation of AI platforms.
Contribute to the development of tools and frameworks to facilitate network optimization.
What We Need to See:
PhD in Computer Science, Computer Engineering, or related field, or equivalent experience
10+ years of experience with a focus on high-performance networking and AI applications
Expertise in RDMA networking (InfiniBand, ROCE), Ethernet, and PCIe.
Experience with at least one high-performance networking library: NCCL, UCX, libfabric, MPI, UCC.
Deep understanding of various aspects of high-performance networking, including network technologies, debugging, and performance analysis.
Experience in developing and optimizing deep learning frameworks such as PyTorch and TensorFlow.
Proficiency in Python and C/C++.
Experience in CUDA programming.
Track record of delivering performance improvements for software used in large-scale deployments.
Knowledge of Kubernetes (k8s) and cloud-native application principles is a plus.
Familiarity with continuous integration and delivery practices for performance optimization.
Ways To stand out from the crowd:
Hands-on experience in optimizing networking building blocks for DL frameworks like PyTorch and TensorFlow.
Experience in developing communication libraries such as NCCL, UCX, UCC, MPI.
In-depth knowledge of RDMA, GPU-Direct, and network technologies.
Provide references to your code contributions.
This is an exceptional opportunity to push the limits of state-of-the-art technology and contribute to the development of platforms the world has never seen before. As part of NVIDIA, you'll work alongside top-tier talent in a collaborative environment that fosters innovation and creativity.
If you're passionate about shaping the future of AI and high-performance computing, apply now to embark on an exciting journey with us!
The base salary range is 220,000 USD - 419,750 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
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NVIDIA is seeking elite ASIC Verification Engineers to verify the design and implementation of the world’s leading SoC's and GPU's. This position offers the opportunity to have real impact in a dynamic, technology-focused company impacting product lines ranging from consumer graphics to self-driving cars and the growing field of artificial intelligence. We have crafted a team of extraordinary people stretching around the globe, whose mission is to push the frontiers of what is possible today and define the platform for the future of computing.
In this position, you will help to build the high-performance processor elements that implement programmable compute and graphics functionality.
What you'll be doing:
As a key member of our ASIC Verification team, you will verify the design and implementation of the industry's leading GPUs
You will be responsible for verification of the ASIC design, architecture, golden models and micro-architecture using advanced verification methodologies such as UVM
Understand the design and implementation of your unit, define the verification scope, develop the verification infrastructure and verify the correctness of the design
Collaborate with architects, designers, and pre and post silicon verification teams to accomplish your tasks
What we need to see:
Bachelors Degree in EE, CS or CE or equivalent experience
5+ years of relevant experience
Experience in verification using random stimulus along with functional coverage and assertion-based verification methodologies
Experience with design and verification tools (VCS or equivalent simulation tools, debug tools like Debussy, GDB)
Expertise in System Verilog or similar HVL
You display strong debugging and analytical skills
Perl and C/C++ programming language experience desirable
Prior experience with arbiters, interconnect networks and/or caches is desirable
Strong communication skills and ability & desire to work as a great teammate are huge plus
Experience in crafting test bench environments for unit and system level verification
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous engineer who loves a challenge? Come join our GPU ASIC Verification team and help us build future architectures that will continue to drive us forward in the fields of computing, graphics and AI.
You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
Official account of Jobstore.
We're looking for a driven, teamwork focused Sr. Security Engineer to help lead our Product Security Operations Center(SOC) team and partner with us to improve NVIDIA’s Cloud Security and Cyber Defense capability.
Do you have validated experience with leading critical initiatives? Do you revel in the challenge of driving the resolution of complex security problems? Showcase your cyber security expertise and passion for innovation to lead and mature our security operations center. You'll assist us in identifying security risks, evolving workflows and processes, while further improving our ability to detect malicious activity. Please come join us!
What you'll be doing:
Reviewing alerts from internal Security Information and Event Management (SIEM) tools requiring log correlation, log analysis, identifying malicious behavior, vetting of False Positives, remediating system misconfigurations and tracking system state changes.
Providing first level response for security events including but not limited to intrusion detection, malicious use of cloud resources, denial of service incidents, privileged account misuse and network breaches
Collaborate across product with sophisticated threat response teams, taking on role of incident commander.
Building automated vulnerability scans and review vulnerability assessment reports
Leading the collection of assets data (configuration settings, running processes, network connections, etc.) for further investigation
Developing new data dashboards and metrics that detail threats to the security posture.
Exploring ways to identify stealthy threats and devise containment processes
Building and maintaining security incident response playbooks and apply them for remediation and recovery efforts
What you should have:
Bachelor's degree (or equivalent experience) in Computer Science, Information Security or a related field
10+ years of hands-on experience in SOC or Security Incident response teams
Outstanding organizational and collaborative focus
Ability to lead in challenging scenarios
Experience with public cloud providers like AWS, GCP and Azure along with their security standard and methodologies is required
Experience with cloud, IaaS, PaaS, ‘network-as-a-service’ environment.
Shown Splunk skills (detection creation, queries and dashboard development)
Demonstrated background in security products (Tenable Nessus, Nexpose) and technologies (Public Key Infrastructure (PKI) systems, authentication and authorization mechanisms, encryption of data in transit and data at rest), modern logging technologies (Splunk and Kibana), security engineering, networking protocols (TCP/UDP), security analysis, network and endpoint forensics
Programming experience in Python, shell scripting to automate and integrate with security tools
Focus on collaboration with excellent verbal and written skills to build effective documentation and streamlined incident reports and RCCA artifacts
Ways to stand out from the crowd:
Validated knowledge and technical savvy with Cloud security controls (security groups, Cloud Trail logs, IAM, EC2, S3, Kubernetes best security practices. etc.)
Understanding of industry compliance standards relevant to Software as a Service and Cloud Computing, such as ISO27001, SOC2, NIST, HIPPA and PCI-DSS
Familiarity with common DevOps technologies such as Ansible, Dockers, Terraform, Kubernetes along with strong Linux fundamentals is a plus
One or more security certifications (CISSP, SSCP, CSSP, GISP, Security+, etc.)
Previous experience in tacking security challenges in a Hybrid cloud environment (workloads spread across on-premise data center and public cloud such as AWS)
You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
Official account of Jobstore.
NVIDIA is hiring software engineers for its Deep Learning Frameworks Sustaining Engineering team. Our team produces software that's powering a revolution in deep learning, enabling breakthroughs in problems from image classification to speech recognition to natural language processing! Help us build software which will be used by the entire world by working directly with deep learning framework developers by integrating with open source code bases.
What you'll be doing:
In this role, responsibilities will include back-porting changes from the mainline branch, keeping track of open source dependency changes, and ensuring the latest stable dependencies are being used for our enterprise products. You will actively contribute changes to the team to support timely Long Term Support releases for the TensorFlow, PyTorch, TensorRT products. The scope of these efforts includes fixing customer reported bugs, integrating bug fixes found in mainline and working with other teams to ensure open source dependencies are patched for security vulnerabilities to address the needs of NVIDIA AI Enterprise business subscribers.
What we need to see:
Bachelors of Science in Computer Science, Deep Learning, Artificial Intelligence, Applied Math, or related field or equivalent experience.
5+ years of relevant software development experience
Excellent C/C++ programming and software design skills, including debugging and open source integration. Python experience also helpful.
Utilizing tools involved in building software (Make, Docker, Bazel), packaging systems (Debian, pip, npm, etc.), Build Systems (Gitlab, CI/Jenkins).
Prior experience with machine learning algorithms and frameworks (TensorFlow, PyTorch, or MXNet).
Ability to work independently, contribute to the stability of releases, and effectively communicate status to those involved in the release in a detail-oriented way.
Ways to stand out from the crowd:
GPU programming experience (CUDA or OpenCL) desired but not required
Experience with contributions to or managing large open source project - use of github, bug tracking, branching and merging code, OSS licensing issues, managing patches, etc.
Familiarity with Gitlab CI pipelines
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative and autonomous, we want to hear from you!
The base salary range is 148,000 USD - 276,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
Official account of Jobstore.
NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities that are hard to solve, that only we can tackle, and that matter to the world. This is our life’s work, to amplify human imagination and intelligence. Make the choice to join us today!
As a member of the GPU/HPC Infrastructure team, you will provide leadership in the design and implementation of ground breaking fast storage solutions to enable runs of demanding deep learning, high performance computing, and computationally intensive workloads. We seek an expert to identify architectural changes and/or completely new approaches for our GPU Compute Clusters fast storage. As an expert, you will help us with the next-gen storage solutions strategic challenges we encounter with storage design for large scale, high performance workloads, evolving our private/public cloud strategy, capacity modelling, and growth planning across our global computing environment.
What you'll be doing:
Research and implementation of distributed storage services.
Design, implement an on-prem HPC infrastructure supplemented with cloud computing to support the growing needs of NVIDIA.
Design and implement scalable and efficient next-gen storage solutions tailored for data-intensive applications, optimizing performance and cost-effectiveness.
Develop tooling to automate management of large-scale infrastructure environments, to automate operational monitoring and alerting, and to enable self-service consumption of resources.
Document the general procedures and practices, perform technology evaluations, related to distributed file systems.
Collaborate across teams to better understand developers' workflows and gather their infrastructure requirements.
Influence and guide methodologies for building, testing, and deploying applications to ensure optimal performance and resource utilization.
Supporting our researchers to run their flows on our clusters including performance analysis and optimizations of deep learning workflows
Root cause analysis and suggest corrective action for problems large and small scales
What we need to see:
Bachelor’s degree in Computer Science, Electrical Engineering or related field or equivalent experience.
8+ years of experience designing and operating large scale storage infrastructure.
Experience analyzing and tuning performance for a variety of HPC workloads.
Experience with one or more parallel or distributed filesystems such as Lustre, GPFS is a must.
Proficient in Centos/RHEL and/or Ubuntu Linux distros including Python programming and bash scripting
Strong Experience operating services in any of the leading Cloud environment [ AWS, Azure or GCP]
Experience with HPC cluster job schedulers such as SLURM, LSF
In depth understating of container technologies like Docker, Enroot
Experience with HPC workflows that use MPI
Ways to stand out from the crowd:
Understanding of MLPerf benchmarking
Familiarity with InfiniBand with IBOP and RDMA
Background with Software Defined Networking and HPC cluster networking
Familiarity with deep learning frameworks like PyTorch and TensorFlow
NVIDIA offers highly competitive salaries and a comprehensive benefits package. We have some of the most resourceful and talented people in the world working for us and, due to unprecedented growth, our extraordinary engineering teams are growing fast. If you're a creative and autonomous engineer with real passion for technology, we want to hear from you.
The base salary range is 180,000 USD - 339,250 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
Official account of Jobstore.
NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities which are hard to solve, that only we can pursue, and that matter to the world. This is our life’s work, to amplify human inventiveness and intelligence.
NVIDIA is looking for best-in-class Senior Physical Design Engineers to join our outstanding Networking Silicon engineering team, developing the industry's best high speed communication devices, delivering the highest throughput and lowest latency! Come and take a part in crafting our groundbreaking and innovating chips, enjoy working in a meaningful, growing and professional environment where you make a significant impact in a technology-focused company.
What you'll be doing:
You will lead all aspects of physical design and implementation of CPU cores and other ASIC IP targeted at the networking markets.
Be exposed and work on variety of complicated designs (including high density and high speed blocks). Resolving complex timing and congestion problems.
Daily work involves all aspects of physical chip development (RTL2GDS) - synthesis, power and clock distribution, place and route, timing closure, power and noise analysis and physical verification.
What we need to see:
Great teammate
BSEE / MSEE or equivalent experience.
5+ years of experience in VLSI physical design implementation on 16nm, 7nm or 5nm technology.
Able to chip in to design flow development and debugging.
Already a validated strong power user of P&R, Timing analysis, Physical Verification and IR Drop Analysis CAD tools from Synopsys (ICC2/DC/PT/STAR/ICV), Cadence (Genus/Innovus/Tempus) and other major EDA companies.
To be successful you should possess strong analytical and debugging skills.
Proficiency using Python, Perl, Tcl, Make scripting is helpful.
NVIDIA is widely considered to be the leader of AI computing, and one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, we want to hear from you.
The base salary range is 128,000 USD - 258,750 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
Official account of Jobstore.
NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 fueled the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new challenges that are hard to address, that only we can pursue, and that matter to the world. This is our life’s work, to amplify human creativity and intelligence. Make the choice to join us today! NVIDIA is seeking a highly skilled and experienced Senior Software Engineer to join our growing team. You will work at the intersection of AI and software engineering, responsible for the design, development, and maintenance of the LLM MLOps platform at Nvidia.
What you'll be doing:
Collaborate across high-performance software engineering teams to develop innovative ML solutions using NVIDIA Deep Learning Software and GPU stack.
Build high performance data pipelines of Big Data solutions in real time for inferencing, training and ETL.
Utilizing Data Engineering, ETL, machine learning technologies for training, inferencing and deployment of ML models into production applications.
Showcase leadership and lead the product development roadmap to align with business priorities and vision.
What we need to see:
Masters in Computer Science, Electrical Engineering or equivalent experience
5+ years of experience architecting, crafting and implementing software solutions, preferably in product development space and 3+ years hands-on experience in distributed computing, data engineering and data analytics.
Solid computer science fundamentals in algorithms/data structures/complexity analyses
Software development experience in any of the following core languages/frameworks: Python, Java, GO, Spring/Hibernate.
Excellent grasp of distributed systems and microservices.
Experience using end-to-end MLOps platforms such as Kubeflow, MLFlow, AirFlow.
Experience with extracting data from storage systems (e.g. Hive, Cassandra, S3, Swiftstack) and understanding of how big data processing systems (e.g. Spark or Map/Reduce) work and help scale the processes.
Solid understanding of Amazon Web Services, Kubernetes, Docker is a plus
Strong communication skills
Ways to stand out from the crowd:
Experience using one or more of the Cloud Based solutions like Kendra, AWS SageMaker, Auto-ML, Big Query, RedShift, Glue, Athena, FireHose etc.
Experience in building and handling MLOps pipelines.
Ability to solve problems using machine learning techniques (statistics, clustering, classification, outlier analysis, etc.). Experience with Deep Learning and LLM prompt engineering or prompt tuning is a plus.
With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry's most desirable employers. We have some of the most forward-thinking and hardworking people in the world working with us and our engineering teams are growing fast in some of the hottest innovative fields: Deep Learning, Artificial Intelligence, and Large Language Models. If you're a creative engineer with a real passion for robust and enjoyable user experiences, we want to hear from you!
The base salary range is 148,000 USD - 276,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
Official account of Jobstore.
NVIDIA's invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company”. We are looking to grow our company, and grow with the smartest people in the world. We are looking for you!
NVIDIA is looking for a Senior Linux Kernel Software Engineer to join the Linux networking drivers R&D team. The work environment is versatile, informative, dynamic and challenging as our employees are currently working on innovative, next-generation network interface card at the forefront of technology in terms of performance.
What you’ll be doing:
Being part of the Linux kernel group, working on developing the device driver for our NICs.
Integration and optimization of existing products and solutions with our software stack and hardware capabilities.
Crafting and developing components of the network, security, and storage software stacks.
Driving a complete engineering process, including refining requirements, engineering design of data structures/algorithms, implementation, peer review, developer testing, and post-GA support.
Drive complex technical issues to closure that may occur in the cross-team boundary.
What we need to see:
Bachelor's degree in Computer Science, or equivalent experience.
5+ years of experience, with strong programming skills in C/C++, and familiarity with object oriented programming concept.
Extensive experience with Linux is required.
Experience with kernel-level programming is required.
Deep understanding of the system software stack, with a focus on software/hardware interaction, including platform firmware, device drivers, Linux kernel, and how user-space applications utilize system services to achieve high performance.
Knowledge of Network Protocols L2/L3/L4 – Ethernet / IP / TCP / UDP.
Ways to stand out from the crowd:
Open source code contributor.
A Master’s or equivalent experience in Computer Science is a plus.
With competitive salaries and a generous benefits package, we are widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our exclusive engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you.
The base salary range is 148,000 USD - 276,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
Official account of Jobstore.
NVIDIA’s deep learning and HPC platforms have made a huge impact in various fields and are broadly used across leading academic institutions, start-ups, and industry, including the world’s largest Internet companies. We need passionate and creative people to help us on building a AI framework that will solve the toughest and most relevant problems of humanity and problems that are at the groundbreaking of science & engineering: weather/climate challenges, product design, digital twins, molecular dynamics, novel materials, accelerated drug development, etc.
What you'll be doing:
Work with some of the brightest minds in a leading AI company to develop a leading machine learning framework, NVIDIA Modulus, for our academic and industrial partners to construct digital twins and machine learning simulation surrogates for real world science and engineering problems
Work with internal project teams to validate applications built using the framework on Nvidia’s products
Stay up to date with the latest research and innovations in deep learning techniques, implement and experiment with new insights to develop and enhance NVIDIA's deep learning technologies with focus on simulations
What we need to see:
BS or MS degree (PhD preferred) in computer science, mathematics, computational science/engineering, or related technical field or equivalent experience.
10+ years of relevant experience.
Strong Python programming skills. Familiarity with containers, numeric libraries, modular software design
Good knowledge of state-of-the-art DNN architectures and machine learning techniques and algorithms (graph networks, diffusion models, reinforcement learning etc.) with experience in developing or using major deep learning frameworks (PyTorch, Tensorflow, JAX etc.)
Experience with solving and using machine learning for real world problems involving scientific/engineering simulations (domains/applications - industrial, life sciences, high energy physics, earth sciences – seismic, weather & climate modeling; physics types - CFD, structural, electromagnetics, optics, acoustics etc.) and/or scientific visualization is a big plus
Strong analytical skills with bias for action. Good time-management and organization skills to thrive in a fast paced, dynamic environment
Solid written and oral communications skills. Good teamwork and interpersonal skills
Ways to stand out from the crowd:
Work with multi-node systems with data-parallel and model parallel programming experience. Experience with CUDA
Usage of nonlinear simulation tools and techniques, usage of major simulation codes (opensource and/or commercial)
Published papers in the field of AI in scientific computing
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative and autonomous, we want to hear from you! NVIDIA’s invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern deep learning — the next era of computing — with the GPU acting as the brain of computers, robots, and self-driving cars that can perceive and understand the world. Today, we are increasingly known as “the AI computing company.” We're looking to grow our company and establish teams with the most thoughtful people in the world.
The base salary range is 180,000 USD - 339,250 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
Official account of Jobstore.
Come be a part of new process technology adoption by joining NVIDIA's Advanced Technology Group! Work as part of the advanced technology team to optimize design tradeoffs and methodology on next generation CMOS technology. We are looking for a Senior ASIC Timing Engineer to join our dynamic and growing team! If you are problem solver and highly motivated individual searching for a collaborative and exciting role, join us today. We encourage applicants with a history of proven success working in a multicultural and diverse environment.
NVIDIA has continuously reinvented itself over two decades. Our invention of the GPU in 1999 sparked the growth of the PC gaming market, redefined modern computer graphics, and revolutionized parallel computing. More recently, GPU deep learning ignited modern AI — the next era of computing. NVIDIA is a “learning machine” that constantly evolves by adapting to new opportunities which are hard to solve, that only we can pursue, and that matter to the world. This is our life’s work, to amplify human inventiveness and intelligence.
What you'll be doing:
You will be responsible for all aspects of timing including, timing analysis and closure, timing environment, setting up constraints and defining the timing methodology for the next generation of designs. This includes working with place and route to understand and implement around their constraints.
Finding the right tradeoffs and balance between frequency and power/area/congestions/yield/etc.
Work on all aspects of DFT/Test timing such as timing constraints, timing analysis, timing convergence, and ECO implementation.
What we need to see:
Hold a BS in Electrical or Computer Engineering or equivalent experience.
5 years experience in Physical design/Timing.
Experience in full-chip/sub-chip Static Timing Analysis (STA), timing constraints generation and management, and timing convergence.
In-depth understanding of multiplexed scan logic and constraints.
Expertise in physical design, optimization, and ECO implementation e.g. cell sizing, buffering, vt swap.
Hands-on knowledge of industry standard Timing/STA EDA tools.
Proficiency in programming and scripting languages, such as TCL and Python.
Ways to stand out from the crowd:
Experience with DFT timing closure for various modes e.g. scan shift, scan capture, transition faults, BIST, etc.
Knowledge of clocking and clock controls in DFT modes.
Experience in methodology or flow development.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and talented people in the world working for us. If you're creative and autonomous, we want to hear from you.
The base salary range is 128,000 USD - 258,750 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
Official account of Jobstore.
NVIDIA is searching for a highly motivated, excellent CAD Engineer to join the Advanced Technologies group. You will develop tools that help improve productivity of custom circuit designers worldwide. A successful candidate will have solid EE background with an in-depth understanding of circuits, layouts and VLSI design. We are looking for someone who loves to write code to automate design processes and who enjoys working in groundbreaking process technologies! A strong background in Skill and Perl are needed for this position. The job involves both development and support. The candidate must have good interpersonal skills.
What you'll be doing:
Develop and support component libraries for advanced process technologies. This will involve developing and maintaining technology files, symbols, gates and pcells, and supporting various netlisters
Install, configure and support foundry PDKs
Maintain the custom design environment used by custom schematic and mask designers
Write scripts using perl, Cadence SKILL, and C++
We use a variety of standard off-the-shelf EDA tools at NVIDIA. You would be responsible for supporting and maintain CAD tools used by IC designers including Virtuoso, IC-Manage, HSPICE, ADE, various simulation tools and Verilog / System Verilog
Work with CAD tool vendors to evaluate new tools, solve bugs, improve usability, etc.
Develop infrastructure to support design work in new process technologies.
What we need to see:
B.S. (or equivalent experience) in Electrical Engineering with 6+ years of experience or M.S. in Electrical Engineering and 3+ year's experience
A basic understanding of mosfet device behavior, CMOS layout, and VLSI design
Excellent programming skills
Experience with perl, Cadence SKILL, tcl
Great communication skills
Passionate about providing excellent support for end-users.
NVIDIA has some of the most forward-thinking and hardworking people in the world working for us and, due to unprecedented growth, our engineering teams are rapidly growing. If you're a creative and autonomous engineer with a real passion for technology, we want to hear from you!
The base salary range is 164,000 USD - 304,750 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
Official account of Jobstore.
NVIDIA is seeking a Senior Supplier Quality Engineer responsible for working with NVIDIA's component suppliers to develop and implement world class supplier quality programs for our AI centric datacenter, automotive and consumer products. This is a meaningful role that will closely work with Hardware Engineering, Product Engineering, and Quality Engineering groups within NVIDIA, as well as our vendors and contract manufacturer partners. The ideal candidate will have stellar analytical skills with a deep rooted structured problem-solving background and show proven experience in failure analysis resolution. Coupled with strong grasps of NPI quality methodologies to bring up supplier quality metrics, this individual shall lead activities properly defining quality expectations at component level.
What you'll be doing:
Responsible for managing end-to-end component quality, working closely with suppliers and internal teams to assure new product readiness and ensure performance meets key quality and reliability metrics.
Establish and lead activities within internal and external teams to ensure proper definition of quality expectations appropriate for each mechanical component. Compile and evaluate data to understand acceptable limits of manufacturing process.
Drive component Failure Analysis activities, including: understanding component failures and defining FA goals, coordinating complete FA work at suppliers’ FA facilities, summarizing and presenting FA results, implementing Corrective Actions and lessons learned following 5-Why practice.
Develop continuous improvement plan with supplier and track/reporting progress for Key Performance Indicators
Lead quality audits at supplier site as needed to ensure supplier quality practice.
Monitor supplier’s alignment to new product introduction schedules to ensure predictable and stable mass production volume ramp.
Quality representative to internal teams, supporting activities for customer quality and internal quality requirements.
Ability to travel domestically/internationally to supplier sites on as needed basis ~10-15%
What we need to see:
B.Sc. or M.Sc. in Engineering (Electrical engineering, Mechanical engineering, Manufacturing Engineering) or equivalent experience
5+ year’s relevant experience in a complex, high-volume manufacturing environment
Knowledge of design, process and manufacturing of interconnect and sensors, specifically cables and connectors for high speed IO applications.
Proven understanding of data driven, statistical QC and QA problem solving methodology
Outstanding communication, multi-tasking and people skill.
Innovative approach to problem solving.
Experience with factory audits.
With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. If you're creative and autonomous, with a genuine passion for technology, we want to hear from you!
The base salary range is 108,000 USD - 218,500 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
Official account of Jobstore.
Site Reliability Engineering (SRE) is an engineering discipline that involves designing, building, and maintaining large-scale production systems with high efficiency and availability. It encompasses various areas, including software and systems engineering practices, storage, data management, and services. SRE professionals are highly specialized and possess expertise in different domains such as systems, networking, storage, coding, database management, capacity management, continuous delivery, and deployment, as well as open-source cloud-enabling technologies like Kubernetes, containers, and virtualization. Their responsibilities encompass ensuring reliable storage solutions, managing data efficiently, and providing related services to support the overall stability and performance of the production systems.
SRE at NVIDIA ensures that our internal and external facing GPU cloud services have reliability and uptime as promised to the users and at the same time enables developers to make changes to the existing system through careful preparation and planning while keeping an eye on capacity, latency, and performance. SRE is also a mindset and a set of engineering approaches to running better production systems and optimizations. Much of our software development focuses on eliminating manual work through automation, performance tuning, and growing the efficiency of production systems. As SREs are responsible for the big picture of how our systems relate to each other, we use a breadth of tools and approaches to tackle a broad spectrum of problems. Practices such as limiting time spent on reactive operational work, blameless postmortems, and proactive identification of potential outages factor into iterative improvement that is key to product quality and interesting and dynamic day-to-day work. SRE's culture of diversity, intellectual curiosity, problem-solving, and openness is important to its success. Our organization brings together people with a wide variety of backgrounds, experiences, and perspectives. We encourage them to collaborate, think big, and take risks in a blame-free environment. We promote self-direction to work on meaningful projects while striving to build an environment that provides the support and mentorship needed to learn and grow.
What You Will Be Doing:
Assist in the design, implementation, and support of large-scale storage clusters, including monitoring, logging, and alerting.
Work with AI/ML workloads to capture and correlate behavior in large clusters and workflows, which are otherwise hard to understand.
Work closely with peers on the team to improve the lifecycle of services – from inception and design, through deployment, operation, and refinement.
Support services before they go live through activities such as system design consulting, developing software and frameworks, capacity management, and launch reviews.
Maintain services once they are live by measuring and monitoring availability, latency, and overall system health, including leveraging machine learning models.
Scale systems sustainably through mechanisms like AI/ML and automation, and evolve systems by pushing for changes that improve reliability and velocity.
Practice sustainable incident response and blameless postmortems.
Be part of an on-call rotation to support production systems.
What We Need To See:
BS degree in Computer Science or related technical field involving coding (e.g., physics or mathematics) or equivalent experience.
At least 5+ years practical experience.
Experience with algorithms, data structures, complexity analysis, software design, and maintaining large-scale Linux-based systems.
Experience in one or more of the following: C/C++, Java, Python, Go, Perl or Ruby, AI/ML frameworks and methodologies.
Good knowledge of infrastructure configuration management tools like Ansible, Chef, Puppet, and Terraform.
Experience in using observability and tracing-related tools like InfluxDB, Prometheus, and Elastic stack.
Ways to stand out from the crowd:
Demonstrated experience in having SRE mindset, customer-first approach, and focus on customer satisfaction and passion for ensuring customer success.Experience with Git, code review, pipelines, and CI/CD.
Interest in crafting, analyzing, and fixing large-scale distributed systems. Strong debugging skills with a systematic problem-solving approach to identify complex problems.
Thrive in collaborative environments and enjoy working with various teams. Experience in using or running large private and public cloud systems based on Kubernetes, OpenStack, and Docker. Flexible in adapting to different working styles.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and talented people on the planet working for us. If you're creative and autonomous, we want to hear from you!
The base salary range is 148,000 USD - 276,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
Official account of Jobstore.
At NVIDIA, we are at the forefront of advancing the capabilities of artificial intelligence. We are seeking an ambitious and forward-thinking deep learning researcher to contribute to the development of next-generation optimizations aimed at efficiently serving generative AI at scale. In this role, you will be developing and exploring new cutting-edge AI optimization techniques, operating at the intersection of algorithms, hardware, and software stacks.
As Nvidia makes significant strides in the Datacenter business, our team holds a central role in maximizing the efficiency of our exponentially growing datacenter deployments and establishing a data-driven approach to hardware design and system software development. We collaborate extensively with diverse teams at Nvidia, spanning deep learning research and framework development teams, to silicon architecture. Thriving in such a high-impact, interdisciplinary environment necessitates not only technical proficiency but also a growth mindset and a pragmatic attitude — qualities that fuel our collective success in shaping the future of datacenter technology.
What You'll Be Doing:
Keeping abreast of the latest advancements in generative AI research.
Implementing and benchmarking cutting-edge large language and multi-modal models, analyzing their emergent patterns and system performance bottlenecks.
Pioneering the development of innovative optimizations to effectively lower the operational costs associated with deploying generative AI models at large scale.
Collaborating closely with production teams to incorporate the latest research advancements into cutting-edge hardware and/or software frameworks.
What We Need to See:
A minimum qualification of a Master's degree (or equivalent experience) in Computer Science, Artificial Intelligence, Applied Mathematics, or related fields. PhD a plus
A strong foundation in deep learning, with a particular emphasis on generative models.
6+ years of relevant software development experience in modern deep learning frameworks such as PyTorch.
Growth mindset and pragmatic attitude.
Ways to Stand Out From the Crowd:
Published research or noteworthy contributions to the field of deep learning, particularly around algorithm development for efficient deployment at scale.
Experience with benchmarking accuracy and performance of AI models.
Background with CUDA programming and GPU performance optimizations.
Familiarity with computer architecture and how it relates to AI algorithms development.
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative and autonomous, we want to hear from you!
The base salary range is 180,000 USD - 339,250 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
Official account of Jobstore.
NVIDIA is searching for a creative and highly motivated engineer with expertise in system software to join the GPU Software team. You will design key aspects of our production GPU kernel drivers and embedded SW with a focus on enabling GPUs in the data center. Bringing GPU scale and power to the data center enables transformational new applications – while raising unique challenges requiring novel software and hardware solutions. Join us to build a world class GPU virtualization solution for the cloud and more.
What you'll be doing:
Design, develop and verify features for our next generation GPU driver architecture; collaborating with hardware engineers and fellow software engineers
Lead efforts to restructure the core GPU driver to a data center first architecture; evolving a model where all components were designed to run from within the same OS context, to a layered design with components running across a Guest VM, Host Kernel Driver and Firmware
Multiple opportunities to collaborate and communicate effectively with teams from all around the globe
What we need to see:
BS or MS degree in Computer Engineering, Computer Science, or related degree or equivalent experience
5+ years of relevant software development experience
Proven leadership skills and strong ownership on past projects
Hands on technical experience and demonstrated excellence in an environment with complex software and hardware designs
Exceptional C programming and low-level driver experience; background and strength with complex system-level debugging
Kernel experience with Linux, Android, Chrome, or Windows systems
Familiarity and comfort with computer system architecture, microprocessor, and microcontroller fundamentals (caches, buses, memory controllers, DMA, etc.)
Ways to stand out from the crowd:
Experience as a maintainer or significant contributor to large open source software projects
Knowledge of virtualization platforms (XenServer, KVM, Hyper-V)
Familiarity with kernel level security concepts; this includes testing techniques and a familiarity with static code analysis, dynamic analysis, fuzzing, negative testing and other techniques
Experience with embedded system SW concepts, e.g.: RTOS and overlay programming models
NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people on the planet working for us. If you're creative, passionate and self-motivated, we want to hear from you! NVIDIA is leading the way in groundbreaking developments in Artificial Intelligence, High-Performance Computing and Visualization. The GPU, our invention, serves as the visual cortex of modern computers and is at the heart of our products and services.
The base salary range is 148,000 USD - 276,000 USD. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions.You will also be eligible for equity and benefits. NVIDIA accepts applications on an ongoing basis.
Official account of Jobstore.
