Senior ML Engineer, Metropolis

NVIDIA
Santa Clara
Workplace: OnsiteFull timeUSD 184,000 - 356,500 annuallyFunction: Data Science & Machine LearningExperience: 8+ yearsEducation: mastersSkills: ["Clarity","Accountability","Cross-functional collaboration","Research-driven problem solving","Execution in parallel workstreams"]

Build and deliver Metropolis physical AI capabilities powered by Cosmos world foundation models, focusing on intelligent video analytics, perception, and real-world deployment needs. Identify Cosmos gaps and propose improvements using synthetic data, tuning, and architecture enhancements. Partner with the Cosmos team and broader product/engineering/data teams to prioritize platform features, lead open-sourcing of artifacts, and continually apply advances in foundation models to production ML development and deployment.

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FursaFursa
NVIDIA
NVIDIA
1 day ago

Senior ML Engineer, Metropolis

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Source: Company careers pageValidated by: Fursa AI
Last checked: 17 hours agoStatus: Live

Job Summary

Build and deliver Metropolis physical AI capabilities powered by Cosmos world foundation models, focusing on intelligent video analytics, perception, and real-world deployment needs. Identify Cosmos gaps and propose improvements using synthetic data, tuning, and architecture enhancements. Partner with the Cosmos team and broader product/engineering/data teams to prioritize platform features, lead open-sourcing of artifacts, and continually apply advances in foundation models to production ML development and deployment.
Location: Santa Clara
Workplace: Onsite
Employment Type: Full time
Job Function: Data Science & Machine Learning
Seniority: Mid level

Key Responsibilities

  • •Build and deliver Metropolis AI solutions powered by Cosmos world foundation models for real-world video analytics, perception, and physical AI requirements.
  • •Find Cosmos underperformance or missing capabilities and recommend new solutions using synthetic data, tuning methods, and architecture improvements.
  • •Partner with the Cosmos team to identify and prioritize platform features aligned to the Metropolis product roadmap.
  • •Lead open-sourcing of solutions and research artifacts developed by the team.
  • •Stay current with advances in foundation models and training methodologies and bring relevant insights back to the team while collaborating across product, program, engineering, and data procurement.

Pay and Benefits

Salary: USD 184,000 - 356,500 annually
Equity and Bonus:Equity

Key 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, including hands-on experience with diffusion models and generative architectures.
  • •Experience with 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:8+ yearsAI researchComputer visionGenerative AIFoundation modelsPhysical AI
Education:Master's
Skills:ClarityAccountabilityCross-functional collaborationResearch-driven problem solvingExecution in parallel workstreams
Tech Stack:CosmosDiffusion modelsGenerative architecturesLLMsVision-language modelsVLMsWorld foundation modelsWFMsIsaac SimCUDATritonModel compressionQuantizationReal-time inferenceLarge-scale data pipelinesMulti-node training

Company Brief

NVIDIA
Designs and manufactures GPUs, AI accelerators, and system-on-chip products for gaming, data centers, professional visualization, and automotive markets, enabling advanced graphics, AI, and high-performance computing solutions worldwide.
Industry: Electronics Manufacturing
Company Size: Enterprise (1,001+ employees)
Revenue: USD 1B+
Growth: Public Company
Valuation: Public Company (Market Cap in USD)
Funding: IPO / Publicly Listed
Headquarters: Santa Clara, United States
Founded: 1993
Glassdoor
Glassdoor: 4.3
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