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      "title": "Senior Deep Learning Compiler Engineer",
      "link": "https://nvidia.wd5.myworkdayjobs.com/NVIDIAExternalCareerSite/job/US-CA-Santa-Clara/Senior-Deep-Learning-Compiler-Engineer_JR2016814",
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      "description": "NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world\n\nWe are looking for a Deep Learning Compiler Engineer. NVIDIA is hiring software engineers for its Deep Learning Compiler (DLC) team. Academic and commercial groups around the world are using GPUs to power a revolution in deep learning, enabling breakthroughs in many areas, e.g. large language models, generative AIs, recommendation systems, image classification, speech recognition, etc. Our DLC has been the backbone of NVIDIA inference engine, spanning across data centers, personal devices, automotive, and robotics. The compiler must deliver leading inference performance, fast build time, reduced memory footprints, and ease of use in the forms of both Ahead-of-Tine and Just-in-Time. Join the team building the DLC which will be used by the entire deep learning community.\n\nWhat you'll be doing:\n\n- Analyzing deep learning networks and developing compiler optimization algorithms.\n\n- Collaborating with members of the deep learning software framework teams and the hardware architecture teams to accelerate the next generation of deep learning software.\n\n- Scope of these efforts includes defining public APIs, performance optimizations and analysis, crafting and implementing compiler infrastructure techniques for neural networks, and other general software engineering work.\n\nWhat we need to see:\n\n- Bachelors, Masters or Ph.D. in Computer Science, Computer Engineering, related field or equivalent experience\n\n- 3+ years of relevant work or research experience in performance analysis and compiler optimizations.\n\n- Ability to work independently, define project goals and scope, and lead your own development efforts.\n\n- Excellent C/C++ and Python programming and software design skills, including debugging, performance analysis, and test design.\n\n- Strong interpersonal skills are required along with the ability to work in a dynamic product-oriented team.\n\nWays to stand out from the crowd:\n\n- Proficient in CPU and/or GPU architecture. CUDA or OpenCL programming experience.\n\n- Experiences in systems with constrained resources, such as embedded platforms, small memory size, and cross compilation.\n\n- Experience with the following technologies: MLIR, XLA, TVM, LLVM, deep learning models and algorithms, and deep learning frameworks, such as PyTorch.\n\n- GPU kernel generation with high performance and fast build time.\n\n- A track record of success in mentoring junior engineers and interns is a bonus.\n\nWith 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 brilliant and hardworking people in the world working with us and our product lines are growing fast in some of the hottest state of the art fields such as Virtual Reality, Artificial Intelligence, Deep Learning and Autonomous Vehicles.\n\nYour base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD.\nYou will also be eligible for equity and benefits.\n\nApplications for this job will be accepted at least until October 13, 2026.\nThis posting is for an existing vacancy.\nNVIDIA uses AI tools in its recruiting processes.\n\nNVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.\n\n#deeplearning",
      "description_html": "<p>NVIDIA has been transforming computer graphics, PC gaming, and accelerated computing for more than 25 years. It’s a unique legacy of innovation that’s fueled by great technology—and amazing people. Today, we’re tapping into the unlimited potential of AI to define the next era of computing. An era in which our GPU acts as the brains of computers, robots, and self-driving cars that can understand the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be immersed in a diverse, supportive environment where everyone is inspired to do their best work. Come join the team and see how you can make a lasting impact on the world</p><p></p><p>We are looking for a Deep Learning Compiler Engineer. NVIDIA is hiring software engineers for its Deep Learning Compiler (DLC) team. Academic and commercial groups around the world are using GPUs to power a revolution in deep learning, enabling breakthroughs in many areas, e.g. large language models, generative AIs, recommendation systems, image classification, speech recognition, etc. Our DLC has been the backbone of NVIDIA inference engine, spanning across data centers, personal devices, automotive, and robotics. The compiler must deliver leading inference performance, fast build time, reduced memory footprints, and ease of use in the forms of both Ahead-of-Tine and Just-in-Time. Join the team building the DLC which will be used by the entire deep learning community.</p><p></p><p><b>What you&#39;ll be doing:</b></p><ul><li><p>Analyzing deep learning networks and developing compiler optimization algorithms.</p></li><li><p>Collaborating with members of the deep learning software framework teams and the hardware architecture teams to accelerate the next generation of deep learning software.</p></li><li><p>Scope of these efforts includes defining public APIs, performance optimizations and analysis, crafting and implementing compiler infrastructure techniques for neural networks, and other general software engineering work.</p></li></ul><p></p><p><b>What we need to see:</b></p><ul><li><p>Bachelors, Masters or Ph.D. in Computer Science, Computer Engineering, related field or equivalent experience</p></li><li><p>3&#43; years of relevant work or research experience in performance analysis and compiler optimizations.</p></li><li><p>Ability to work independently, define project goals and scope, and lead your own development efforts.</p></li><li><p>Excellent C/C&#43;&#43; and Python programming and software design skills, including debugging, performance analysis, and test design.</p></li><li><p>Strong interpersonal skills are required along with the ability to work in a dynamic product-oriented team.</p></li></ul><p></p><p><b>Ways to stand out from the crowd:</b></p><ul><li><p>Proficient in CPU and/or GPU architecture. CUDA or OpenCL programming experience.</p></li><li><p>Experiences in systems with constrained resources, such as embedded platforms, small memory size, and cross compilation.</p></li><li><p>Experience with the following technologies: MLIR, XLA, TVM, LLVM, deep learning models and algorithms, and deep learning frameworks, such as PyTorch.</p></li><li><p>GPU kernel generation with high performance and fast build time.</p></li><li><p>A track record of success in mentoring junior engineers and interns is a bonus.</p></li></ul><p></p><p>With highly competitive salaries and a comprehensive benefits package, NVIDIA is widely considered to be one of the technology industry&#39;s most desirable employers. We have some of the most brilliant and hardworking people in the world working with us and our product lines are growing fast in some of the hottest state of the art fields such as Virtual Reality, Artificial Intelligence, Deep Learning and Autonomous Vehicles.</p><p style=\"text-align:inherit\"></p><p style=\"text-align:inherit\"></p>Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 152,000 USD - 241,500 USD.<div><div><div><div><div><div><div><p></p><p><span>You will also be eligible for equity and <a href=\"https://www.nvidia.com/en-us/benefits/\" target=\"_blank\">benefits</a>.</span></p><p></p></div></div></div></div></div></div></div>Applications for this job will be accepted at least until October 13, 2026.<p></p><p>This posting is for an existing vacancy. </p><p>NVIDIA uses AI tools in its recruiting processes.</p><p></p>NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.<p style=\"text-align:inherit\"></p><p style=\"text-align:inherit\"></p>#deeplearning",
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      "id": "NVIDIA-2027-Internships--Deep-Learning_JR2023497-1",
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      "title": "NVIDIA 2027 Internships: Deep Learning",
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      "description": "By submitting your resume, you acknowledge that your 2027 Deep Learning internship application will be processed in accordance with NVIDIA’s Applicant Privacy Policy and you agree to our Terms of Service. We’ll review resumes on an ongoing basis, and a recruiter may reach out if your experience fits one of our many internship opportunities.\n\nNVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world's largest industries and profoundly impacting society — from gaming to robotics, self-driving cars to life-saving healthcare, climate change to virtual worlds where we can all connect and create. Our internships offer an excellent opportunity to expand your career and get hands on experience with one of our industry leading Deep Learning teams. We’re seeking strategic, ambitious, hard-working, and creative individuals who are passionate about helping us tackle challenges no one else can solve.\n\nThroughout the 12-week full-time internship, students will work on projects that have a measurable impact on our business. We’re looking for students pursuing a B.S., M.S., or Ph.D. degree within a relevant or related field.\n\nPotential Internships in this field include:\nDeep Learning Applications and Algorithms\n\n- Developing algorithms for deep learning, data analytics, or scientific computing to improving performance of GPU implementations\n\n- Course or internship experience related to the following areas could be required: Deep Neural Networks, Linear Algebra, Numerical Methods and/or Computer Vision, Software Design, Computer Memory (Disk, Memory, Caches), CPU and GPU Architectures, Networking, Numeric Libraries, Embedded System Design and Development, Drivers, Real-Time Software\n\nDeep Learning Frameworks and Libraries\n\n- Building underlying frameworks and libraries to accelerate Deep Learning on GPUs\n\n- Contributing directly to software packages such as JAX, PyTorch, and TensorFlow, integrating the latest library (e.g., cuDNN) or CUDA features, performance tuning, and analysis\n\n- Optimizing core deep learning algorithms and libraries (e.g., CuDNN, CuBLAS), maintaining build, test, and distribution infrastructure for these libraries and deep learning frameworks on NVIDIA supported platforms\n\n- Course or internship experience related to the following areas could be required: Computer Architecture (CPUs, GPUs, FPGAs or other accelerators), GPU Programming Models, Performance-Oriented Parallel Programming, Optimizing for High-Performance Computing (HPC), Algorithms, Numerical Methods\n\nWhat we need to see:\n\n- Must be actively enrolled in a university pursuing a B.S., M.S., or Ph.D. degree in Electrical Engineering, Computer Engineering, or a related field, for the full duration of the internship; anticipated graduation date (month and year) must be clearly indicated on a resume or CV to be considered.\n\n- Depending on the internship role, prior experience or knowledge requirements could include the following programming skills and technologies: C, C++, CUDA, Python, x86, ARM CPU, GPU, Linux, Direct3D, Vulkan, OpenGL, OpenCL, Spark, Perl, Bash/Shell Scripting, Container Tools (Docker/Containers, Kubernetes), Infrastructure Platforms (AWS, Azure, GCP), Data Technologies (Kafka, ELK, Cassandra, Apache Spark), React, Go\n\nClick here to learn more about NVIDIA, our early talent programs, benefits offered to students and other helpful student resources related to our latest technologies and endeavors.\n\nOur internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The hourly rate for our interns is 20 USD - 71 USD.\nYou will also be eligible for Intern benefits. \n\nApplications are accepted on an ongoing basis.\nThis posting is for an existing vacancy.\nNVIDIA uses AI tools in its recruiting processes.\n\nNVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.",
      "description_html": "<p>By submitting your resume, you acknowledge that your 2027 Deep Learning internship application will be processed in accordance with NVIDIA’s <a target=\"_blank\" href=\"https://www.nvidia.com/en-us/about-nvidia/careers/applicant-privacy-policy/\">Applicant Privacy Policy </a>and you agree to our <a target=\"_blank\" href=\"https://www.nvidia.com/en-us/about-nvidia/terms-of-service/\">Terms of Service</a>. We’ll review resumes on an ongoing basis, and a recruiter may reach out if your experience fits one of our many internship opportunities.</p><br /><p>NVIDIA pioneered accelerated computing to tackle challenges no one else can solve. Our work in AI and digital twins is transforming the world&#39;s largest industries and profoundly impacting society — from gaming to robotics, self-driving cars to life-saving healthcare, climate change to virtual worlds where we can all connect and create. Our internships offer an excellent opportunity to expand your career and get hands on experience with one of our industry leading Deep Learning teams. We’re seeking strategic, ambitious, hard-working, and creative individuals who are passionate about helping us tackle challenges no one else can solve. </p><p> </p><p>Throughout the 12-week full-time internship, students will work on projects that have a measurable impact on our business. We’re looking for students pursuing a B.S., M.S., or Ph.D. degree within a relevant or related field. </p><p> </p><p><b>Potential Internships in this field include: </b> </p><p><u>Deep Learning Applications and Algorithms</u> </p><ul><li>Developing algorithms for deep learning, data analytics, or scientific computing to improving performance of GPU implementations </li></ul><ul><li>Course or internship experience related to the following areas could be required: Deep Neural Networks, Linear Algebra, Numerical Methods and/or Computer Vision, Software Design, Computer Memory (Disk, Memory, Caches), CPU and GPU Architectures, Networking, Numeric Libraries, Embedded System Design and Development, Drivers, Real-Time Software </li></ul><br /><p><u>Deep Learning Frameworks and Libraries</u> </p><ul><li>Building underlying frameworks and libraries to accelerate Deep Learning on GPUs </li></ul><ul><li>Contributing directly to software packages such as JAX, PyTorch, and TensorFlow, integrating the latest library (e.g., cuDNN) or CUDA features, performance tuning, and analysis </li></ul><ul><li>Optimizing core deep learning algorithms and libraries (e.g., CuDNN, CuBLAS), maintaining build, test, and distribution infrastructure for these libraries and deep learning frameworks on NVIDIA supported platforms </li></ul><ul><li>Course or internship experience related to the following areas could be required: Computer Architecture (CPUs, GPUs, FPGAs or other accelerators), GPU Programming Models, Performance-Oriented Parallel Programming, Optimizing for High-Performance Computing (HPC), Algorithms, Numerical Methods </li></ul><br /><p><b>What we need to see: </b> </p><ul><li>Must be actively enrolled in a university pursuing a B.S., M.S., or Ph.D. degree in Electrical Engineering, Computer Engineering, or a related field, for the full duration of the internship; <b>anticipated graduation date (</b><u>month and year</u><b>) </b>must be clearly indicated on a resume or CV to be considered. </li></ul><ul><li><b>Depending on the internship role, prior experience or knowledge requirements </b><i>could </i><b>include the following programming skills and technologies: </b>C, C&#43;&#43;, CUDA, Python, x86, ARM CPU, GPU, Linux, Direct3D, Vulkan, OpenGL, OpenCL, Spark, Perl, Bash/Shell Scripting, Container Tools (Docker/Containers, Kubernetes), Infrastructure Platforms (AWS, Azure, GCP), Data Technologies (Kafka, ELK, Cassandra, Apache Spark), React, Go </li></ul><p> </p><p>Click <a target=\"_blank\" href=\"https://www.nvidia.com/content/dam/en-zz/Solutions/about-nvidia/careers/UR-Student-Resources.pdf\"><u>here</u><b> </b></a>to learn more about NVIDIA, our early talent programs, benefits offered to students and other helpful student resources related to our latest technologies and endeavors. </p><p style=\"text-align:inherit\"></p><p style=\"text-align:inherit\"></p>Our internship hourly rates are a standard pay based on the position, your location, year in school, degree, and experience. The hourly rate for our interns is 20 USD - 71 USD.<p style=\"text-align:inherit\"></p><p style=\"text-align:left\"><span><span>You will also be eligible for Intern</span></span><span><span> </span><a href=\"https://www.nvidia.com/en-us/benefits/interns/\" target=\"_blank\"><span><span>benefits</span></span></a>. </span><span><span></span></span></p><p style=\"text-align:inherit\"></p><p style=\"text-align:inherit\"></p>Applications are accepted on an ongoing basis.<p></p><p>This posting is for an existing vacancy. </p><p>NVIDIA uses AI tools in its recruiting processes.</p><p></p>NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.<p></p><p></p>",
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