Senior MLOps Engineer - DSX Enablement

NVIDIA
Bengaluru, Hyderabad, Pune
Workplace: OnsiteFull timeFunction: Solutions Engineering & Sales EngineeringExperience: 8+ yearsEducation: bachelorsSkills: ["Communication","Technical presentation","Engineering discipline","Execution","Problem-solving"]

Build and deploy custom AI solutions on NeoCloud and NVIDIA Cloud Partners, covering distributed training, inference optimization, and end-to-end MLOps pipelines. Serve as a primary technical contact for customers and partners to ensure success on DGX Cloud, while collaborating with teams across infrastructure software and accelerated frameworks. Profile and tune large-scale workloads to reduce latency, cost, and operational risk, and develop open-source tools and reference architectures for scalable ML systems.

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FursaFursa
NVIDIA
NVIDIA
3 days ago

Senior MLOps Engineer - DSX Enablement

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Source: Company careers pageValidated by: Fursa AI
Last checked: 4 hours agoStatus: Live

Job Summary

Build and deploy custom AI solutions on NeoCloud and NVIDIA Cloud Partners, covering distributed training, inference optimization, and end-to-end MLOps pipelines. Serve as a primary technical contact for customers and partners to ensure success on DGX Cloud, while collaborating with teams across infrastructure software and accelerated frameworks. Profile and tune large-scale workloads to reduce latency, cost, and operational risk, and develop open-source tools and reference architectures for scalable ML systems.
Location: Bengaluru, Hyderabad, Pune
Workplace: Onsite
Employment Type: Full time
Job Function: Solutions Engineering & Sales Engineering
Seniority: Mid level

Key Responsibilities

  • •Build and deploy custom AI solutions on NeoCloud and NVIDIA Cloud Partners, including distributed training, inference optimization, and MLOps pipelines.
  • •Act as a primary technical contact for internal and external customers and partners, guiding joint engagements and solving complex production problems.
  • •Collaborate with teams building infrastructure software and accelerated frameworks that support AI applications.
  • •Profile and tune large-scale training and inference workloads on NCP platforms to reduce latency, cost, and operational risk.
  • •Develop open-source tools and reference architectures for scalable ML/AI workloads, pipelines, and systems.

Key Requirements

  • •BS, MS, or Ph.D. in Computer Science, Computer/Electrical Engineering, or a related technical field, or equivalent experience.
  • •8+ years of experience in technical roles such as data science, data engineering, or ML engineering, ideally for large-scale production systems.
  • •AI/ML experience across the machine learning lifecycle, from exploratory analysis to production systems.
  • •Systems experience with Linux, batch schedulers, Kubernetes, distributed filesystems, and advanced datacenter networking.
  • •Scripting/programming skills in bash and Python, plus systems programming skills in C++, Go, or Rust.
Experience:8+ years
Education:Bachelor's
Skills:CommunicationTechnical presentationEngineering disciplineExecutionProblem-solving
Tech Stack:NeoCloudNVIDIA Cloud Partners (NCPs)DGX CloudDGXCUDANeMoRAPIDSTritonNIMLinuxBatch schedulersKubernetesDistributed filesystemsAdvanced networkingInfiniBandNVLinkRoCEBashPythonC++

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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