Research Scientist Spatial Intelligence - New College Grad jobs at Nvidia in Canada, Old Toronto

What you’ll be doing:

• Write safe, scalable, modular, and high-quality (C++/Python) code for our core backend software for LLM inference.

• Perform benchmarking, profiling, and system-level programming for GPU applications.

• Provide code reviews, design docs, and tutorials to facilitate collaboration among the team.

• Conduct unit tests and performance tests for different stages of the inference pipeline.

What we need to see:

• Bachelor's degree in Computer Science, Computer Engineering, relevant technical field, or equivalent experience.

• Strong coding skills in Python and C/C++.

• Knowledgeable and passionate about machine learning and performance engineering.

• Proven project experiences in building software where performance is one of its core offerings.

Ways to stand out from the crowd:

• Solid fundamentals in machine learning, deep learning, operating systems, computer architecture and parallel programming.

• Research experience in systems or machine learning.

• Project experience in modern DL software such as PyTorch, CUDA, vLLM, SGLang, and TensorRT-LLM.

• Experience with performance modelling, profiling, debug, and code optimization or architectural knowledge of CPU and GPU.

We strongly encourage you to include sample projects (e.g. Github) that demonstrate the qualifications above.

What you’ll be doing:

• Invent or apply deep learning techniques to the field of 3D or 4D content creation (photogrammetry, generative AI).

• Work on improving realism and immersive qualities of VR environments and interactions, including creating content with AI techniques, intelligent characters, and behavior of crowds and traffic.

• Participate in projects to conduct Deep Learning research and publish papers to well known conferences (ex. CVPR, NeurIPS)

• Research dedicated to developing deep learning technology for Games, Virtual Reality, and other applications.

What we need to see:

• Currently pursuing a B.S., Master’s or Ph.D. in Electrical Engineering, Computer Science/Engineering,Math/Physics/Statisticsor a related field

• Past experience in cross collaborative environments.

• Minimum 1 course on theories and practices of machine learning, including common machine learning frameworks

Requirements if pursuing a Master’s or PhD:

• In-depth knowledge of the theory and practice of machine learning

• Minimum 1 strong publication record (NeurIPS, ICML, AAAI, CVPR, ECCV, ICCV, etc).

• Knowledge of common machine learning frameworks

• Track record of research excellence

You will also be eligible for Intern

What you will be doing:

• Develop and optimize diffusion-based generative models for high-fidelity, controllable image/video synthesis.

• Design scalable architectures that reduce inference latency and enable real-time or interactive generation workflows.

• Contribute to fundamental research and publish in top-tier conferences such as CVPR, NeurIPS, ICLR, ICCV, or SIGGRAPH.

• Collaborate across teams to integrate research into simulation systems, digital avatars, robotics, and other NVIDIA platforms.

What we need to see:

• PhD or equivalent experience in Computer Science, Computer Vision, Machine Learning, or a related field.

• Strong foundation in generative models.

• Experience with Python and PyTorch, and large-scale model training workflows.

• Ability to conduct independent research and communicate findings clearly.

• Passion for innovation in vision AI and a drive to see ideas move from research to impact.

Ways to stand out from the crowd:

• Skills in efficient model architectures and efficient implementations.

• Sharp mathematics skills.

What you’ll be doing:

• Develop and evaluate novel perception approaches from synthetic simulation on robotics tasks that optimize for learning performance and generalizability.

• Develop benchmarks to validate robot task performance and generalizability to novel scenarios and out-of-distribution events.

• Collaborate with research and engineering teams across NVIDIA such as GR00T and IsaacLab to integrate and validate novel approaches to robot training.

What we need to see:

• Pursuing a BS or MS in Computer Science or related field.

• Experience in software development with Python and the deep-learning software stack (Pytorch, Tensorflow, Jax, etc.).

• Background with reinforcement learning, imitation learning, sensor simulation and synthetic data generation.

Ways to stand out from the crowd:

• Prior experience with Isaac Sim, Isaac Lab, Isaac Gym, or Mujoco.

• You have already trained a robot in simulation and deployed the policy sim-to-real.

• Publications in major AI and robotics conferences.

You will also be eligible for Intern