LLM Engineer, Agentic Researcher Platform

NVIDIA
Ho Chi Minh City, Hanoi
Full timeFunction: Research & Scientific (R&D)Experience: 3+ yearsEducation: mastersSkills: ["Technical leadership","Mentoring","Problem-solving","Communication","Teamwork"]

Build NVIDIA’s autonomous, agentic platform that optimizes machine-learning models end-to-end—from model architecture and hyperparameters to the CUDA/Triton code the platform compiles. Drive AI-native workflows for research, experimentation, evaluation, and deployment, and create benchmarking frameworks measuring accuracy, latency, memory, throughput, and cost. Design for reproducibility, AI safety, sandboxing, and compute-cost governance while mentoring engineers across research, engineering, and product teams.

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FursaFursa
NVIDIA
NVIDIA
2 months ago

LLM Engineer, Agentic Researcher Platform

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Source: Company careers pageValidated by: Fursa AI
Last checked: 16 hours agoStatus: Live

Job Summary

Build NVIDIA’s autonomous, agentic platform that optimizes machine-learning models end-to-end—from model architecture and hyperparameters to the CUDA/Triton code the platform compiles. Drive AI-native workflows for research, experimentation, evaluation, and deployment, and create benchmarking frameworks measuring accuracy, latency, memory, throughput, and cost. Design for reproducibility, AI safety, sandboxing, and compute-cost governance while mentoring engineers across research, engineering, and product teams.
Location: Ho Chi Minh City, Hanoi
Employment Type: Full time
Job Function: Research & Scientific (R&D)
Seniority: Mid level

Key Responsibilities

  • •Develop and advance a self-governing, agentic platform to optimize AI models end-to-end, including GPU code generation.
  • •Use AI-native and agentic workflows to accelerate research, experimentation, evaluation, and deployment.
  • •Establish and run benchmarking frameworks to measure accuracy, latency, memory, throughput, and cost, including head-to-head comparisons.
  • •Design and deploy with reproducibility, AI safety, sandboxing, and compute-cost governance in mind.
  • •Lead technical initiatives, mentor engineers, and collaborate closely across research, engineering, and product teams to build a One Team culture.

Key Requirements

  • •Master’s degree in Computer Science, AI, Electrical Engineering, or equivalent experience.
  • •3+ years building and deploying ML, LLM, or model-optimization systems.
  • •Strong Python skills with hands-on experience using PyTorch (or TensorFlow).
  • •Hands-on experience with automated experimentation such as hyperparameter optimization, AutoML, or NAS.
  • •Experience building LLM-agent systems (reasoning, tool use, multi-step orchestration) and/or production ML pipelines and MLOps infrastructure.
Experience:3+ yearsMLLLMsModel optimizationMLOpsAgentic AIAutoMLNAS
Education:Master's
Skills:Technical leadershipMentoringProblem-solvingCommunicationTeamwork
Tech Stack:PythonPyTorchTensorFlowCUDATritonNeMoTAONIMNemotronAutoMLNASMLOpsHyperparameter optimizationMAP-ElitesBayesian optimizationHyperbandASHATorch.compileOperator fusionQuantization

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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