# LLM Engineer, Agentic Researcher Platform

**Company**: NVIDIA
**Location**: Ho Chi Minh City
**Experience**: senior
**Job type**: full-time
**Category**: Engineering
**Industry**: Technology

**Apply**: https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/Vietnam-Ho-Chi-Minh-City/LLM-Engineer--Agentic-Researcher-Platform_JR2021274?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/jobs/job_8d7a58f4-258

## Description

NVIDIA is seeking a Machine Learning Engineer to help build the core of an autonomous, agentic platform that optimizes machine-learning models end-to-end. The platform optimizes the model itself (architecture, hyperparameters) and its implementation (the CUDA/Triton code it compiles to) across domains.

Responsibilities:

- Develop and advance a self-governing, agentic platform that optimizes AI models end-to-end , architecture, hyperparameters, and the GPU code they compile to.

- Leverage AI-native and agentic workflows to accelerate research, experimentation, evaluation, and deployment of AI systems.

- Establish and drive benchmarking frameworks that measure accuracy, latency, memory footprint, throughput, and cost , including head-to-head comparisons that prove the agent beats existing automated search.

- Design and deploy with strong consideration for reproducibility, AI safety, sandboxing, and compute-cost governance.

- Lead technical initiatives, mentor engineers, and foster a One Team culture through close collaboration across research, engineering, and product teams.

Requirements:

- Master's degree in Computer Science, AI, Electrical Engineering, or equivalent experience.

- 3+ years of experience building and deploying ML, LLM, or model-optimization systems.

- Strong Python skills and hands-on experience with PyTorch (or TensorFlow).

- Hands-on experience with automated experimentation , hyperparameter optimization, AutoML, or NAS.

- Experience building LLM-agent systems (reasoning, tool use, multi-step orchestration) and/or production ML pipelines and MLOps infrastructure.

- Proven technical leadership and mentoring experience, and strong problem-solving, communication, and teamwork skills.

Preferred qualifications:

- Hands-on experience with NVIDIA AI technologies such as NeMo, TAO, Triton, CUDA, NIM, and Nemotron.

- Experience building agentic AI systems with reasoning, tool use, and code generation.

- Expertise in optimization: evolutionary and quality-diversity search (e.g. MAP-Elites), Bayesian optimization, and multi-fidelity methods (Hyperband/ASHA).

- GPU performance work , CUDA/Triton kernels, torch.compile, operator fusion, quantization , and interest in inference-efficiency domains such as AI-RAN.

- Experience benchmarking AI systems for accuracy, latency, memory, reliability, and cost. A research track record (publications or credible reproductions) in AutoML, NAS, LLM agents, or optimization.

## Skills

### Required
- Python
- PyTorch
- TensorFlow
- automated experimentation
- hyperparameter optimization
- AutoML
- NAS
- LLM-agent systems
- production ML pipelines
- MLOps infrastructure

### Nice to have
- NeMo
- TAO
- Triton
- CUDA
- NIM
- Nemotron
- agentic AI systems
- reasoning
- tool use
- code generation
- optimization
- evolutionary search
- quality-diversity search
- Bayesian optimization
- multi-fidelity methods
- GPU performance
- inference-efficiency

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Source: [Apply at nvidia.wd5.myworkdayjobs.com](https://nvidia.wd5.myworkdayjobs.com/en-US/NVIDIAExternalCareerSite/job/Vietnam-Ho-Chi-Minh-City/LLM-Engineer--Agentic-Researcher-Platform_JR2021274?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)