below marketmost similar roles pay hereabove market
This role pays more than
68%
of similar roles. Most pay
$193,225–$254,750
— the blue band above.
At the midpoint, this role pays about
$236k
versus about
$224k
for comparable roles.
Based on 240 similar postings.
Employer
About Nvidia
Nvidia is a leading designer of graphics processing units (GPUs) and system-on-chip units, powering gaming, professional visualization, data centers, and artificial intelligence workloads. Industry: Semiconductors & AI Computing
Nvidia currently has
1814 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 1204 roles with salary data.
The Senior Vision Language Model Engineer joins the team to design and build agentic data and training workflows for Autonomous Vehicles, Robotics, and Medical applications. This role involves partnering with researchers to develop and evaluate prototypes for vision language models and vision language action models focused on video search and understanding. Key responsibilities include designing agentic workflows to automate data discovery, labeling, and retraining while curating high-quality multimodal datasets involving video, sensor, and language traces. The position requires building and productizing new data sources like simulation and synthetic data. Candidates must possess expertise in transformer-based architectures, deep learning frameworks, and Python. The work addresses technical problems in physical AI, specifically improving dataset search platforms and model training capabilities for autonomous driving, healthcare, and robotics.
Develop and evaluate prototypes of vision language models (VLMs) and vision-language-action models (VLAs).
Design and implement agentic data workflows to automate data discovery, labeling, evaluation, and retraining.
Build, curate, and maintain high-quality multimodal datasets for autonomous driving, healthcare, and robotics.
Explore and productize new data sources, including simulation and synthetic data.
Apply agentic AI workflows across the full applied research lifecycle to improve development velocity.
Contribute to the development of NVIDIA Cosmos Dataset Search and other core platform products.
Train and deploy deep learning models using distributed training, data preprocessing, and iterative debugging.
What we're looking for
PhD with 4+ years, MS with 6+ years, or BS with 8+ years of experience in Computer Science, Computer Engineering, or a related technical field.
Strong background in modern deep learning, including transformer-based architectures, video modeling, and multimodal VLM/VLA or foundation models.
Excellent experience training and deploying deep learning models on real-world datasets, including data preprocessing, distributed training, evaluation, and debugging.
Excellent experience with Python and at least one deep learning framework.
Current with the latest research on image and video search in autonomous vehicles, healthcare, robotics, or related physical AI applications.
Fluent with agentic AI workflows across the full applied research lifecycle, including prototyping novel algorithms and search pipelines.
Clear and effective communication skills with experience working in a dynamic, product- and research-focused team.
Strong track record publishing in top-tier conferences, patents in video retrieval, or experience in robotic systems (preferred).
Machine Learning
Computer Vision
Deep Learning
Python
C++
PyTorch
JAX
TensorFlow
TensorRT
ONNX
Linux
Object Detection
SLAM
LIDAR Sensor Fusion
Model Pruning
System Profiling