Remote AI Platform Engineer - Scalable ML Inference

Bright Vision Technologies; Charlotte (NC); On-site; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking a highly experienced AI Platform Engineer with 10+ years in distributed systems, cloud-native infra, and AI platforms. You will design, build, and operate enterprise-scale AI inference platforms and ML services, with deep focus on LLM serving, GPU optimization, Kubernetes, and MLOps.

The role emphasizes scalable, secure, and cost-efficient AI platforms to support production workloads, with remote-friendly, high-impact collaboration across teams.

Qualifications

• 10+ years of professional experience in distributed systems, infrastructure, or ML platform engineering.
• Strong programming in Python and at least one systems language such as Go, Rust, or C++.
• Extensive experience with LLM serving, model inference optimization, and production AI infra.

Responsibilities

• Design, build, and maintain scalable AI inference and model-serving platforms for enterprise production envs.
• Architect cloud-native infra supporting LLMs, foundation models, and ML services.
• Optimize latency, throughput, GPU usage, memory, and scheduling across AI workloads.
• Design autoscaling, workload orchestration, traffic management, and routing for AI services.
• Implement model deployment, versioning, rollback, and lifecycle management using MLOps.
• Develop observability, logging, tracing, and alerting for platform reliability.

Skills

Python

Go

Rust

C++

LLM serving

Kubernetes

Cloud platforms

GPU optimization

MLOps

Distributed systems

Education

Bachelor's or Master's in Computer Science / Computer Engineering / AI or related

Tools

vLLM

TensorRT-LLM

Triton Inference Server

Ray Serve

Job description

Bright Vision Technologies is seeking a highly experienced AI Platform Engineer with 10+ years in distributed systems, cloud-native infra, and AI platforms. You will design, build, and operate enterprise-scale AI inference platforms and ML services, with deep focus on LLM serving, GPU optimization, Kubernetes, and MLOps.

The role emphasizes scalable, secure, and cost-efficient AI platforms to support production workloads, with remote-friendly, high-impact collaboration across teams.