Analytical Scientist jobs

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

• 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'll be doing:

• Develop new Deep Learning models for automatic speech recognition, speech synthesis, neural machine translation and natural language

• Design new large scale training algorithm

• Open-source models using NeMo conversational AI frameworks

• Mentor interns

• Publish research papers on top speech and NLP conferences

• Collaborate with universities and research teams.

What we need to see:

• PhD in Computer Science or Electrical Engineering (or equivalent experience)

• Proven understanding of Deep Learning for Natural Language Processing or Speech Recognition

• At least 5 years of research experience in speech recognition or NLP

• Excellent Python programming skills

• Experience with PyTorch

• Strong publications record

Ways to stand out from the crowd:

• Contribution to open-source projects

• Being reviewers for one of the top speech conferences

As a Research Scientist specializing in Generative AI for Physical AI, you'll be at the forefront of developing next-generation algorithms that bridge the gap between virtual and physical realms. You'll work with state-of-the-art technology and have access to massive computational resources to bring your ideas to life.

What you'll be doing:

• Pioneer revolutionary generative AI algorithms for physical AI applications, with a focus on advanced video generative models and video-language models

• Architect and implement sophisticated data processing pipelines that produce premium-quality training data for Generative AI and Physical AI systems

• Design and develop cutting-edge physics simulation algorithms that enhance Physical AI training

• Scale and optimize large-scale training systems to efficiently harness the power of 20,000+ GPUs for training foundation models

• Author influential research papers to share your groundbreaking discoveries with the global AI community

• Drive innovation through close collaboration with research teams, diverse internal product groups, and external researchers

• Build lasting impact by facilitating technology transfer and contributing to open-source initiatives

What we need to see:

• PhD in Computer Science, Computer Engineering, Electrical Engineering, or related field (or equivalent experience).

• Deep expertise in PyTorch and related libraries for Generative AI and Physical AI development

• Strong foundation indiffusion, vision language and reasoning models and their applications

• Proven experience with reinforcement learning algorithms and implementations

• Robust knowledge of physics simulation and its integration with AI systems

• Demonstrated proficiency in 3D generative models and their applications

Ways to stand out from the crowd:

• Publications or contributions to major AI conferences (ICLR, NeurIPS, ICML, CVPR, ECCV, SIGGRAPH, ICCV, etc.)

• Experience with large-scale distributed training systems

• Background in robotics or physical systems

• Open-source contributions to prominent AI projects

• History of successful research-to-product transitions