This role pays more than
51%
of similar roles. Most pay
$200,887–$254,750
— the shaded band above.
At the midpoint, this role pays about
$236k
versus about
$228k
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
896 open roles
on FindRole.
Listed pay typically runs
$184,000–$287,500
across 876 roles with salary data.
As a Senior ML Engineer on the Metropolis team, you will develop and deliver next-generation intelligent video analytics and perception solutions for smart cities, industrial automation, and autonomous systems. You will construct production-quality AI capabilities by leveraging Cosmos world foundation models to solve real-world physical AI challenges. Your daily responsibilities include identifying model performance gaps, generating synthetic data, refining tuning methods, improving architectures, and collaborating with the Cosmos team to expand platform features. The role requires deep expertise in deep learning fundamentals, diffusion models, generative architectures, and large-scale foundation models including LLMs and VLMs. You will utilize simulation environments like Isaac Sim while managing the end-to-end machine learning development lifecycle. Key technical skills include experience with model compression, quantization, real-time inference optimization, and potentially CUDA or Triton for accelerating inference pipelines in physical settings.
Build and deliver production-quality Metropolis AI solutions using Cosmos world foundation models for video analytics and physical AI.
Identify areas where Cosmos models underperform and propose improvements through synthetic data generation, tuning methods, and architectural refinements.
Collaborate with the Cosmos team to prioritize and develop platform features aligned with the Metropolis product roadmap.
Lead the open-sourcing of research artifacts and solutions to contribute to the broader AI community.
Monitor and integrate the latest advancements in foundation models, generative architectures, and training methodologies into team workflows.
Coordinate with Product, Program, Engineering, and Data Procurement teams to align goals and unblock project execution.
What we're looking for
Master's degree or PhD in Computer Science, Electrical Engineering, or a related field (or equivalent experience).
8+ years of proven experience in applied machine learning or AI research.
Deep expertise in deep learning fundamentals with hands-on experience in diffusion models and generative architectures.
Experience pre-training or refining large language models, vision-language models, or world foundation models.
Experience working with large-scale foundation models including training workflows, fine-tuning techniques, and evaluation approaches.
Experience working with simulation environments like Isaac Sim or similar platforms.
End-to-end understanding of the ML development and deployment lifecycle using modern AI tools and workflows.
Experience in model compression, quantization, real-time inference optimization, or distributed infrastructure (preferred); published research or open-source contributions (preferred).
C++
Python
Linux
Computer Vision
Deep Learning
PyTorch
CUDA
TensorRT
Distributed Systems
Microservices
Containers
GPU Acceleration
Multi-threading
Asynchronous I/O
Omniverse
Unreal Engine
Unity
World Foundation Models
LLMs
VLMs
Multimodal Generative Models
Diffusion Models
Robotics
Autonomous Vehicles
Synthetic Data Generation
CUDA-X
Isaac Sim
Isaac Lab
OpenUSD
Omniverse
Deep Learning
Sim-to-Real
Video Generation