Senior ML Engineer, Metropolis

NVIDIA•Us, CA

About The Position

NVIDIA's Metropolis team advances physical AI by building intelligent video analytics and perception solutions for smart cities, industrial automation, and autonomous systems at scale. We seek a Senior ML Engineer to compose and deliver next-generation Metropolis solutions powered by Cosmos, NVIDIA's world foundation model platform. Your main task will be constructing production-quality AI capabilities for Metropolis by demonstrating Cosmos to address real-world perception and physical AI challenges. You will also partner closely with the Cosmos team to develop and broaden the platform’s features aligned with the Metropolis product roadmap. If you are driven to push generative AI, simulation, and large-scale model development forward and want your work to impact real-world systems, we invite you to apply.

Requirements

MSc 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 in pre-training or refining large language models (LLMs), vision-language models (VLMs), or world foundation models (WFMs).
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.
Consistent track record of leading projects end-to-end and delivering results with clarity and accountability.
Ability to manage and complete tasks across multiple parallel workstreams in a fast-paced, evolving environment.
End-to-end understanding of ML development and deployment life cycle with the ability to quickly adopt and bring to bear modern AI development tools and workflows.

Nice To Haves

Hands-on experience with model compression, quantization, and real-time inference optimization for production deployments.
Previous experience implementing AI solutions in physical settings such as public areas, smart infrastructure, or robotics platforms.
Experience scaling AI systems across distributed infrastructure, including multi-node training and large-scale data pipelines.
Published research or open-source contributions in relevant areas such as generative models, synthetic data, or physical AI.
Familiarity with CUDA, Triton, or low-level GPU kernel development for inference pipeline acceleration.

Responsibilities

Build and deliver innovative Metropolis AI solutions powered by Cosmos world foundation models, addressing real-world requirements in intelligent video analytics, perception, and physical AI.
Find areas where Cosmos models underperform or lack capability and recommend new solutions. These involve generating synthetic data, refining tuning methods, and improving architecture. Metropolis use cases serve as the main reference.
Partner with the Cosmos team to identify and prioritize new platform features guided by the Metropolis product roadmap, contributing to deliverables that support the wider ecosystem.
Lead the open-sourcing of solutions and research artifacts developed by the team, contributing to the broader AI and research community.
Stay current with the latest advances in foundation models, generative architectures, and training methodologies, and actively bring relevant insights back to the team.
Partner multi-functionally with Product, Program, Engineering, and Data Procurement teams to drive alignment and unblock execution.