Senior AI Infrastructure Engineer

NVIDIA
Tel Aviv
Workplace: OnsiteFull timeFunction: Research & Scientific (R&D)Experience: 5+ yearsEducation: bachelorsSkills: ["Communication","Collaboration","Problem-solving"]

Senior AI/MLOps Engineer to build and maintain production-ready infrastructure for AI models and agents in a security/networking research context. Collaborates with data scientists, software engineers, security architects, and DevOps to deploy, optimize, and monitor AI models at scale, create training/inference pipelines, and integrate with CI/CD to ensure high availability and performance in production environments.

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FursaFursa
NVIDIA
NVIDIA
4 months ago

Senior AI Infrastructure Engineer

✓ Verified Job

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

Source: Company careers pageValidated by: Fursa AI
Last checked: 23 hours agoStatus: Live

Job Summary

Senior AI/MLOps Engineer to build and maintain production-ready infrastructure for AI models and agents in a security/networking research context. Collaborates with data scientists, software engineers, security architects, and DevOps to deploy, optimize, and monitor AI models at scale, create training/inference pipelines, and integrate with CI/CD to ensure high availability and performance in production environments.
Location: Tel Aviv
Workplace: Onsite
Employment Type: Full time
Job Function: Research & Scientific (R&D)

Key Responsibilities

  • •Developing, improving and optimizing scalable infrastructure for handling and deploying security and networking AI models and agents in production, ensuring high availability, scalability, reproducibility, and performance.
  • •Optimizing AI models and agents for performance, scalability, and resource utilization, considering latency, efficiency, and cost.
  • •Monitoring and deploying agentic systems, LLMs, and ML models in production.
  • •Designing and implementing frameworks/pipelines for AI training, inference, and experimentation.
  • •Collaborating with data scientists, security architects and software engineers to operationalize and deploy AI models and agents, including packaging and integration with existing systems; participate in code/design reviews and test plans.

Key Requirements

  • •BSc/MSc in CS/CE or related field (or equivalent experience)
  • •5+ years of experience deploying and monitoring AI/ML models, LLMs and agents to production in distributed multi-node environments
  • •Proficiency in Python, Java, or Scala with ML/AI frameworks (TensorFlow, PyTorch)
  • •Proficiency in microservices, container orchestration, cloud platforms, and scalable infrastructure for training and inference
  • •Knowledge of CI/CD tools (GitLab, GitHub Actions, Jenkins)
Experience:5+ yearsAIMLMLOpsProduction systemsDistributed systems
Education:Bachelor's
Skills:CommunicationCollaborationProblem-solving
Tech Stack:PythonJavaScalaTensorFlowPyTorchKubernetesDockerGitLabGitHub ActionsJenkins

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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