Job description

For more than 25 years, NVIDIA has been driving innovation in computer graphics, PC gaming, and accelerated computing. It’s a distinctive heritage of creativity driven by excellent technology—and outstanding people. Today, we’re harnessing the boundless capabilities of AI to build the next era of computing. An era where our GPU serves as the intelligence behind computers, robots, and autonomous vehicles that perceive the world. Doing what’s never been done before takes vision, innovation, and the world’s best talent. As an NVIDIAN, you’ll be part of a varied, encouraging environment where everyone is motivated to perform at their highest level. Join our team and discover how you can build a lasting impact on the world. 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. What you'll be doing: • 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. What we need to see: • 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. Ways to stand out from the crowd: • 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. With a competitive salary package and benefits, NVIDIA is widely considered to be one of the technology world’s most desirable employers. We have some of the most forward-thinking and hardworking people in the world working for us. Are you a creative and autonomous Systems Software Engineer who loves challenges? Do you have a genuine passion for advancing the state of Computer Vision 3D across a variety of industries? If so, we want to hear from you. Your base salary will be determined based on your location, experience, and the pay of employees in similar positions. The base salary range is 184,000 USD - 287,500 USD for Level 4, and 224,000 USD - 356,500 USD for Level 5. You will also be eligible for equity and benefits . Applications for this job will be accepted at least until August 21, 2026. This posting is for an existing vacancy. NVIDIA uses AI tools in its recruiting processes. NVIDIA is committed to fostering an inclusive work environment and proud to be an equal opportunity employer. As we highly value diversity in our current and future employees, we do not discriminate (including in our hiring and promotion practices) on the basis of race, religion, color, national origin, gender, gender expression, sexual orientation, age, marital status, veteran status, disability status or any other characteristic protected by law.

Requirements

Must-haves

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.
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.
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.
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.
You will also be eligible for equity and benefits .
Applications for this job will be accepted at least until August 21, 2026.
This posting is for an existing vacancy.
NVIDIA uses AI tools in its recruiting processes.

Nice-to-haves

None flagged.

Application prep

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Keywords to mirror

aimlmachine learning

Platform: eightfold
Effort: medium

Benefits

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Vision