Principal Applied Research Scientist Quantum Supercomputing jobs at Nvidia

What you'll be doing:

• Path-find technical innovations in Quantum Error Correction and Fault Tolerance, working with multi-functional teams in Product, Engineering, and Applied Research

• Develop novel approaches to quantum error correction codes and their logical operations, including methods for implementation and logical operation synthesis

• Research and co-design improved methods to achieve fault tolerance, such as techniques for logical operations, concatenation, synthesis, distillation, cultivation, or others

• Collaborate with internal teams and external partners on developing technology components to enable a fault-tolerant software stack integrated with quantum hardware

• Adopt a culture of collaboration, rapid innovation, technical depth, and creative problem solving

What we need to see:

• Degree in Physics, Computer Science, Chemistry, Applied Mathematics, or related engineering field or equivalent experience (Ph.D. preferred)

• Extensive background in Quantum Information Science with 8+ overall years of experience in the Quantum Computing industry

• A demonstrated ability to deliver high impact value in quantum error correction and fault tolerance

Ways to stand out from the crowd:

• Hands-on experience in scientific computing, high-performance computing, applied machine learning, or deep learning

• Experience with co-design of quantum error correction with quantum hardware or quantum applications

• Experience with CUDA and NVIDIA GPUs

• Passion to drive technology innovations into NVIDIA software and hardware products to support Quantum Computing

NVIDIA is searching for a world-class researcher in generative AI to join our research team. You will be conducting original research for generative AI applications, including image generation, video generation, 3D generation, and audio generation. You will be working with a team of world-class researchers eager to make great impacts with generative AI models. You will be building research prototypes and scaling them with large datasets and compute. After building prototypes that demonstrate the promise of your research, you will work with product teams to help them integrate your ideas into products.

What you'll be doing:

• Conduct original research in the space of generative AI

• Implement and train large-scale generative AI models for various content creation applications

• Collaborate with other research team members, a diverse set of internal product teams, and external researchers

• Have a broader impact through the transfer of the technology you've developed to relevant product groups

What we need to see:

• Ph.D. in Computer Science/Engineering, Electrical Engineering, or a related field (or equivalent experience).

• 5+ years of relevant research experience.

• Excellent collaboration and interpersonal skills

• Excellent python/C++ programming skills

• Great knowledge of common deep-learning frameworks

• Experience in processing or curating large-scale datasets

• Excellent knowledge of theory and practice of deep learning, computer vision, natural language processing, or computer graphics

• Track record of research excellence or significant product development

What you'll be doing:

• Path-find technical innovations in Quantum Error Correction and Fault Tolerance, working with multi-functional teams in Product, Engineering, and Applied Research

• Develop novel approaches to decoding quantum error correction codes and their logical operations, including researching advanced implementations in hardware

• Research and co-design improved methods to achieve more scaled decoders

• Collaborate with internal teams and external partners on developing technology components to enable a fault-tolerant software stack integrated with quantum hardware

• Adopt a culture of collaboration, rapid innovation, technical depth, and creative problem solving

What we need to see:

• Masters degree in Physics, Computer Science, Chemistry, Applied Mathematics, or related engineering field or equivalent experience (Ph.D. preferred)

• Extensive background in Quantum Information Science with 6+ overall years of experience in the Quantum Computing industry

• A demonstrated ability to deliver high impact value in quantum error correction and decoding

Ways to stand out from the crowd:

• Hands-on experience in scientific computing, high-performance computing, applied machine learning, or deep learning

• Experience with co-design of quantum error correction with quantum hardware or quantum applications

• Experience with CUDA and NVIDIA GPUs

• Passion to drive technology innovations into NVIDIA software and hardware products to support Quantum Computing

What you'll be doing:

• Path-find technical innovations in Quantum Error Correction and Fault Tolerance, working with multi-functional teams in Product, Engineering, and Applied Research

• Develop novel approaches to quantum error correction codes and their logical operations, including methods for implementation and logical operation synthesis

• Research and co-design improved methods to achieve fault tolerance, such as techniques for logical operations, concatenation, synthesis, distillation, cultivation, or others

• Collaborate with internal teams and external partners on developing technology components to enable a fault-tolerant software stack integrated with quantum hardware

• Adopt a culture of collaboration, rapid innovation, technical depth, and creative problem solving

What we need to see:

• Masters degree in Physics, Computer Science, Chemistry, Applied Mathematics, or related engineering field or equivalent experience (Ph.D. preferred)

• Extensive background in Quantum Information Science with 12+ overall years of experience in the Quantum Computing industry

• A demonstrated ability to deliver high impact value in quantum error correction and fault tolerance

Ways to stand out from the crowd:

• Hands-on experience in scientific computing, high-performance computing, applied machine learning, or deep learning

• Experience with co-design of quantum error correction with quantum hardware or quantum applications

• Experience with CUDA and NVIDIA GPUs

• Passion to drive technology innovations into NVIDIA software and hardware products to support Quantum Computing

What you'll be doing:

• Define and drive architecture for complex, high-volume GPU products, ensuring they meet our ambitious performance and scalability goals.

• Perform and guide power and performance evaluation, trade-off assessments, and architectural modeling to identify optimal chip, package and system construction.

• Lead improvements in architecture, methodology and tools to improve the scalability of our system, collaborating closely with cross-functional engineering teams.

• Specify and optimize SoC subsystems such as memory architecture, test infrastructure and power management.

• Collaborate with RTL, verification, physical design, firmware, and software teams to successfully implement and integrate system components.

• Produce high-quality technical documentation of SoC architecture, specifications, and development trade-offs.

• Provide technical leadership and mentorship to junior architects and engineers, encouraging a culture of excellence and innovation.

What we need to see:

• Over 15 years in SoC architecture development or similar technical leadership roles.

• Proven track record of defining and delivering multiple high-volume SoC systems (such as CPU, GPU, modem, networking or similar).

• Proficiency in evaluating power/performance and architectural modeling in high-level programming languages.

• Strong understanding of SoC system fundamentals, including memory hierarchy, coherency, clocking, power domains, boot and reset, test, and debug methodologies.

• Hands-on experience with silicon bring-up, debug and tuning.

• Excellent interpersonal, leadership, and collaboration skills, with the ability to influence across organizations.

• Outstanding documentation, written, and verbal communication skills.

• Master's degree (or equivalent experience) in a relevant subject area: Computer Science, Electrical Engineering or Computer Engineering

Ways to stand out from the crowd:

• Experience with GPU or AI accelerator architecture, including platform aspects, off-chip I/O technologies, and networked multi-GPU systems

• Knowledgeable in modern packaging technologies, and their costs and benefits

• Knowledgeable in AI workload characteristics

• Outstanding analytical and problem-solving skills with a focus on optimizing performance, power, area, and complexity.

What you’ll be doing

• Designing and training large-scale machine learning models at the intersection of genomics, proteomics, and chemistry

• Experimental design for probing the capabilities and limitations of the foundation models that are developed

• Mentoring other team members, leading research initiatives, and helping to craft strategic roadmaps

• Working closely with hardware and software teams to improve NVIDIA’s platforms for large-scale foundation model applications

• Engaging with the broader research community via publications, presentations, and research collaborations

What we need to see:

• PhD (or equivalent experience) in Computer Science or Computational Biology

• 4+ years in deep learning, bioinformatics, chemical engineering, structural biology, or related fields.

• Track record of excellence in engineering and research

• Deep understanding of modern AI techniques: deep learning for sequences, diffusion models, LLMs, unsupervised learning. Hands-on practical know-how of how to design, train, and evaluate large neural networks.

• Excellent software engineering and design instincts in Python, C++, or similar.

• Outstanding expertise in biochemistry, drug discovery, molecular biology, chemical engineering, or related fields

What you will be doing:

• Collaborating with researchers, partners, and customers to break new ground in accelerated quantum chemistry simulation software

• Stay on top of developments in your fields of expertise through conferences and publications and share this with relevant teams at NVIDIA

What we need to see:

• PhD or equivalent experience in CS, EE (or other related technical field)

• 8+ overall years of experience in developing high-performance numerical methods for scientific computing and quantum chemistry at supercomputer scales

• Proven track record working within development teams with impactful results

• Good knowledge of CPU and/or GPU hardware architecture

Ways to stand out from the crowd:

• Good understanding of DFT, CCSD, Hartree-Fock, and other quantum chemistry domain techniques

• Experience with SW/product development in HPC or Datacenter domains and familiarity with GPU compute programming model frameworks such as CUDA, OpenCL, HIP

• Familiarity withPre-silicon/Post-siliconSW development life cycle and tools