Tech Stack
Tag name is followed by "@" symbol and proficiency level value.
About proficiency levels:
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
AI @ 4
Agentic AI @ 6
Algorithms @ 6
Communication @ 4
Debugging @ 4
Deep Learning @ 7
Python @ 4
Robotics @ 4
- 1-2 — basic awareness. Minimal hands-on experience, and a rudimentary understanding of the technology's purpose;
- 3-6 — daily use. Comfortable and regular usage, capable of handling common tasks and challenges related to the technology;
- 7-9 — you are an expert, you can teach others, you know all the pitfalls and tricks;
- 10 — exceptional knowledge, comprehensive understanding, and adeptness in all aspects of the technology, including advanced problem-solving. Think twice before claiming or demanding such level.
Details
NVIDIA is seeking a senior vision language model engineer to design and build agentic data and training workflows for autonomous vehicles, robotics, and medical applications. The role focuses on developing scalable dataset search platforms and model training capabilities for physical AI developers.
Responsibilities
- Partner with researchers to develop and evaluate prototypes of vision-language models (VLMs) and vision-language-action models (VLAs) for video search, video understanding, and related applications.
- Design and implement agentic data workflows that automate data discovery, labeling, evaluation, and retraining.
- Build, curate, and maintain high-quality multimodal datasets, including video, sensor data, and language/action traces, for end-to-end physical AI applications such as autonomous driving.
- Explore and productize new data sources, including simulation and synthetic data.
- Use agentic AI workflows across the full applied research lifecycle.
- Collaborate with research, model development, performance, and product teams.
- Contribute to NVIDIA Cosmos Dataset Search and other core NVIDIA platforms and products.
Requirements
- PhD with 4+ years, MS with 6+ years, or BS or equivalent experience with 8+ years of relevant experience in Computer Science, Computer Engineering, or a related technical field.
- Strong background in modern deep learning, including transformer-based architectures, video modeling, multimodal VLM/VLA systems, or foundation models.
- Extensive experience training and deploying deep learning models on real-world datasets, including data preprocessing, distributed training, evaluation, debugging, and iterative improvement.
- Excellent Python experience and experience with at least one deep learning framework.
- Knowledge of current research on image and video search in autonomous vehicles, healthcare, robotics, or related physical AI applications.
- Fluency with agentic AI workflows across the applied research lifecycle, including prototyping novel algorithms and search pipelines, benchmarking, and integrating prototypes into production codebases.
- Clear and effective communication skills, with experience working in dynamic, product- and research-focused teams.
Preferred Qualifications
- Publication record at top-tier conferences such as CVPR, NeurIPS, ICML, or ECCV.
- Patents in video retrieval or a related field.
- Strong coding architecture skills demonstrated through contributions to large internal or open-source projects.
- Experience with robotic systems such as autonomous vehicles or humanoid robotics.
Compensation and Benefits
The expected base salary ranges are USD 184,000–287,500 for Level 4 and USD 224,000–356,500 for Level 5. The role also includes eligibility for equity and benefits.
Applications will be accepted at least until November 8, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes and is an equal opportunity employer.
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