全职 AI Infrastructure Engineer 工作, 薪水, Top Gen AI Jobs 公司招聘中 - Ricebowl

Home/Jobs/AI Infrastructure Engineer

AI Infrastructure Engineer

Pokee AI

Singapore

3+ years

Today

$130K–150K/yr

Full-time

Remote

Skills Required

vLLM

TensorRT-LLM

Python

Rust

C++

Go

TensorRT

Triton

ONNX Runtime

Kubernetes

Docker

AWS

GCP

GPU computing

distributed systems

Description

Pokee AI is hiring an AI Infrastructure Engineer to build and optimize the systems behind RL-trained AI agents. The role focuses on scalable training, high-performance inference serving, and production infrastructure for enterprise use.

Company: Pokee AI

Role: AI Infrastructure Engineer

Location: Remote (US/Singapore Preferred)

Experience

• 3+ years of experience in ML infrastructure, ML platform engineering, or a related systems role
• Strong proficiency in Python and systems-level languages such as Rust, C++, or Go
• Hands-on experience with ML serving frameworks such as vLLM, TensorRT, Triton, or ONNX Runtime
• Experience with container orchestration and cloud infrastructure such as Kubernetes, Docker, AWS, or GCP
• Solid understanding of GPU computing, distributed systems, and performance profiling
• Familiarity with ML experiment tracking and pipeline orchestration tools such as MLflow, Weights & Biases, or Airflow
  
  

Responsibilities

• Build and optimize scalable training and inference infrastructure for RL-based AI agent models
• Optimize model serving for latency, throughput, and cost across cloud and on-device deployments
• Develop and manage CI/CD pipelines, experiment tracking, and model versioning systems
• Implement data pipelines for training data collection, preprocessing, and reward signal computation
• Collaborate with research scientists to productionize new algorithms and model architectures
• Ensure infrastructure meets enterprise requirements for reliability, security, and compliance
  
  

Additional Responsibilities

• Support cloud, on-premise, and on-device deployments
• Align infrastructure with enterprise reliability, security, and compliance needs
  
  

Nice To Have

• Experience with on-device or edge inference optimization such as GGUF quantization, TensorRT-LLM, CoreML, or QNN
• Familiarity with on-premise GPU deployments such as NVIDIA DGX, Dell PowerEdge, or Lenovo ThinkStation
• Experience supporting RL training loops or online learning systems in production
• Background in enterprise software with knowledge of security and compliance frameworks
• Contributions to open-source ML infrastructure projects
  
  

More Skills

performance profiling, MLflow, Weights & Biases, Airflow, CI/CD pipelines, experiment tracking, model versioning, data pipelines, reward signal computation, RL-based AI agent models, SOC 2, data residency

Prepare for this role

Recommended resources to build the skills for this position. Sponsored.

Top 15 Together AI Interview Questions

Zenaique

A Together AI-focused interview question set from Zenaique.

Top 25 xAI Interview Questions

Zenaique

An xAI-focused interview question set from Zenaique.

Top 25 LLM Evaluation Interview Questions

Zenaique

Curated LLM evaluation questions covering benchmarks, evals, and human review.

More vLLM jobs

AI Engineer

Ditto

San Francisco

4 days ago

Lead AI Engineer

Bridge-it

Delhi

6 days ago

Software AI Engineer

Tredence

Bengaluru

11 days ago

Staff Software AI Engineer

Equinix

Bengaluru

12 days ago

Senior AI/ML Engineer

AlifCloud IT Consulting Pvt. Ltd.

Pune

16 days ago

Senior System Software Engineer - Local AI

Nvidia

Pune

17 days ago