- MS or PhD in Computer Science, Electrical/Computer Engineering, Robotics, or a related field, or equivalent experience.
- 12+ years of proven experience building deep learning systems in Python with PyTorch or JAX on Linux.
- Deep expertise in 3D computer vision, multi-view geometry, structure-from-motion or SLAM, depth and camera pose estimation, point cloud processing, or 3D reconstruction with the practical ability to produce and validate 3D ground truth at scale, not just consume it.
- Hands-on experience with vision-language models, including building the training data and evaluations that measurably improve visual grounding and reasoning quality.
- Demonstrated experience building large-scale multimodal data pipelines: distributed video and image processing, deduplication, captioning and annotation, automated quality metrics, and dataset versioning.
- Experience running and validating large model training on multi-GPU, multi-node clusters, with working knowledge of distributed training and sharding strategies such as data, tensor, and pipeline parallelism or FSDP.
- Rigorous evaluation methodology: designing benchmarks that resist gaming, building clean ablations, and reading results honestly enough to kill your own ideas.
- Excellent written and verbal communication, with a track record of partnering effectively with research scientists and translating research direction into engineering execution.
Ways to stand out from the crowd
- PhD and/or publications at CVPR, ICCV, ECCV, NeurIPS, ICLR, or CoRL in 3D vision, multimodal learning, or embodied AI.
- Experience curating web-scale or petabyte-scale video corpora, and building the distributed processing infrastructure behind it using Ray, Spark, Slurm, or similar.
- Familiarity with 3D foundation models and modern auto-labeling techniques for geometry, camera estimation, and correspondence.
- Experience with vision-language model post-training, supervised fine-tuning, chain-of-thought data design, reward modeling, or reinforcement learning with verifiable rewards applied to reasoning quality.
- Experience building evaluation infrastructure and harnesses such as VLMEvalKit, including leaderboards, dashboards, and example-level failure inspection.
With competitive salaries and a generous 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 versatile people in the world working with us, and our engineering teams are growing fast in some of the most impactful fields of our generation: Deep Learning, Artificial Intelligence, and Physical AI. If you're a creative engineer who enjoys autonomy and shares our passion for technology, we want to hear from you!
Your base salary will be determined based on your location, experience, and other objective job-related factors. The expected base salary range for this position is 224,000 USD – 356,500 USD.
You will also be eligible for equity and benefits.
Applications for this job will be accepted at least until November 3, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.