ML and Agentic Systems Engineer

NVIDIA
Santa Clara
Workplace: OnsiteFull timeUSD 224,000 - 431,250 annuallyFunction: IT Operations (Systems/Network Admin)Experience: 12+ yearsEducation: mastersSkills: ["System design","Testing","Debugging","Collaboration","Code maintainability"]

Build agentic systems for the ML lifecycle—data generation/curation, evaluation, debugging, training orchestration, and iterative improvement. You’ll create AI-native software where models and agents interact with codebases, tools, experiments, and environments, and design scalable evaluation platforms using metrics, human feedback, and agent-driven analysis. Own and evolve large Python and PyTorch codebases, and deliver multimodal ML pipelines from data processing through deployment.

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FursaFursa
NVIDIA
NVIDIA
2 days ago

ML and Agentic Systems Engineer

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI
Last checked: 14 hours agoStatus: Live
Reposted: similar role first listed 5 months ago

Job Summary

Build agentic systems for the ML lifecycle—data generation/curation, evaluation, debugging, training orchestration, and iterative improvement. You’ll create AI-native software where models and agents interact with codebases, tools, experiments, and environments, and design scalable evaluation platforms using metrics, human feedback, and agent-driven analysis. Own and evolve large Python and PyTorch codebases, and deliver multimodal ML pipelines from data processing through deployment.
Location: Santa Clara
Workplace: Onsite
Employment Type: Full time
Job Function: IT Operations (Systems/Network Admin)

Key Responsibilities

  • •Design and implement agentic workflows across the ML lifecycle, including data generation/curation, evaluation, debugging, training orchestration, and iteration.
  • •Build AI-native systems where models and agents interact with codebases, tools, experiments, and environments to improve productivity.
  • •Create self-improving loops where agents generate data, surface failures, evaluate outputs, and drive better decisions.
  • •Own and evolve large-scale Python and PyTorch codebases, turning fast-moving ideas into robust, modular software.
  • •Design and scale evaluation platforms combining automated metrics, human feedback, and agent-driven analysis.

Pay and Benefits

Salary: USD 224,000 - 431,250 annually
Equity and Bonus:Equity

Key Requirements

  • •Significant experience building machine learning systems and software platforms, not just models.
  • •Expert-level Python skills, with strong judgment on modularity, abstraction boundaries, and long-term code health.
  • •Deep familiarity with PyTorch, including debugging, adapting, and extending model behavior within larger software systems.
  • •Experience building ML pipelines and evaluation/developer tooling/workflow automation at meaningful scale.
  • •Strong software engineering fundamentals across system design, testing, packaging, debugging, and collaborative codebase evolution.
Experience:12+ yearsMachine learningMultimodal AILLM-based systems
Education:Master's in Computer Science, Engineering, or related field
Skills:System designTestingDebuggingCollaborationCode maintainability
Tech Stack:PythonPyTorchLLMAgent workflowsTool useEvaluation platformsOpen-sourceData pipelinesTraining orchestrationBenchmarkingDeploymentAuthNAuthZIAM

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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