RL ML Infrastructure Engineer - Scalable, Low-Latency

Pokee AI; United States; Remote; USD 140,000 - 220,000; Full time

Job summary

Pokee AI seeks an experienced ML infrastructure engineer to design and maintain the core platform that trains and serves reinforcement-learning agents at production scale. You will own scalable training pipelines, low-latency inference, and robust infrastructure across cloud and edge environments.

Collaborate with research scientists to productionize new algorithms, optimize latency and throughput on AWS or GCP, and ensure security/compliance for enterprise workloads.

Qualifications

• 3+ years in ML infrastructure or ML platform engineering.
• Strong Python and systems-level language experience.
• Hands-on ML serving frameworks expertise.
• Experience with container orchestration and cloud infra (AWS/GCP).
• Familiarity with experiment tracking and pipeline tools.

Responsibilities

• Architect and operate training and inference infrastructure for RL models.
• Tune serving for latency, throughput, and cost across cloud and edge deployments.
• Build and maintain CI/CD, experiment tracking, and model versioning.
• Develop data pipelines for training data collection and preprocessing.
• Collaborate with research to productionize new algorithms.

Skills

Python

Rust

C++

Go

ML serving frameworks

Kubernetes

Docker

AWS/GCP

GPU computing

MLflow

Weights & Biases

Airflow

Tools

NVIDIA TensorRT

ONNX Runtime

vLLM

Triton

CUDA

Job description

Pokee AI seeks an experienced ML infrastructure engineer to design and maintain the core platform that trains and serves reinforcement-learning agents at production scale. You will own scalable training pipelines, low-latency inference, and robust infrastructure across cloud and edge environments.

Collaborate with research scientists to productionize new algorithms, optimize latency and throughput on AWS or GCP, and ensure security/compliance for enterprise workloads.