AI Infrastructure Engineer

Pokee AI Inc; Singapore; On-site; SGD 80,000 - 100,000; Full time

Job summary

A cutting-edge AI technology firm in Singapore is seeking an AI Infrastructure Engineer to design and optimize infrastructure for RL-trained AI agents. The role involves building scalable training and inference systems, developing CI/CD pipelines, and collaborating on new algorithms with research scientists. Ideal candidates will have 3+ years of experience in ML infrastructure, strong proficiency in Python, and familiarity with frameworks like vLLM and TensorRT. Join this elite team and shape the future of enterprise AI.

Qualifications

• 3+ years of experience in ML infrastructure or related systems role.
• Strong proficiency in Python and systems-level languages like Rust, C++, or Go.
• Hands-on experience with ML serving frameworks.

Responsibilities

• Design, build, and maintain scalable ML infrastructure.
• Optimize model serving for latency and throughput.
• Develop and manage CI/CD pipelines and experiment tracking.

Skills

Python

Rust

C++

Go

Kubernetes

Docker

GPU computing

distributed systems

Tools

vLLM

TensorRT

Triton

ONNX Runtime

MLflow

Weights & Biases

Airflow

Job description

As an AI Infrastructure Engineer, you will build and optimize the systems that power Pokee’s RL‑trained AI agents—from scalable training pipelines to high‑performance inference serving across cloud and on‑device deployments. You’ll ensure that our research breakthroughs translate into production infrastructure that enterprises can rely on.

What You'll Do

• Design, build, and maintain scalable training and inference infrastructure for RL‑based AI agent models
• Optimize model serving for latency, throughput, and cost across cloud (AWS, GCP) and on‑premise/on‑device environments
• Develop and manage CI/CD pipelines, experiment tracking, and model versioning systems
• Implement efficient 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 (SOC 2, data residency)

What We're Looking For

Required

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

Bonus Points

• Experience with on‑device / edge inference optimization (GGUF quantization, TensorRT‑LLM, CoreML, QNN)
• Familiarity with on‑premise GPU deployments (NVIDIA DGX, Dell PowerEdge, 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

Who You Are

You want to join a small, elite team solving one of the hardest problems in AI—building agents that actually work in the real world. You’ll have direct impact on the product, access to cutting‑edge research, and the opportunity to shape the future of enterprise AI from the ground up.

Apply for AI Infrastructure Engineer

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