Senior Remote Model Serving Engineer

Bright Vision Technologies; Naperville (IL); Remote; USD 74,000 - 98,000; Full time

Job summary

Bright Vision Technologies is seeking a Model Serving Engineer to design, build, and operate high-performance inference platforms for serving large machine learning models in production. The role focuses on the systems engineering side of AI deployment, including request routing, batching, caching, autoscaling, GPU utilization, and end-to-end observability across diverse model workloads.

The ideal candidate brings strong distributed systems and performance engineering expertise, has shipped

Qualifications

• Bachelor’s or Master’s degree in Computer Science or related field.
• 7+ years of experience in distributed systems, infrastructure, or ML platform engineering.
• Proficiency in Python and a systems language (Go, Rust, or C++).
• Hands-on experience with LLM or large model inference frameworks such as vLLM or TensorRT-LLM.
• Strong understanding of GPU architecture, memory hierarchies, and accelerator utilization.
• Familiarity with Kubernetes, autoscaling, and modern cloud platforms.
• Experience with observability stacks including metrics, tracing, and structured logging.
• Solid grounding in performance engineering and capacity planning.
• Strong communication and incident response skills.

Responsibilities

• Design, build, and operate high-performance ML inference platforms for production.
• Optimize latency, throughput, cost, and quality trade-offs in ML serving.
• Implement routing, batching, caching, autoscaling, and observability across model workloads.
• Collaborate with cloud and platform teams to maintain reliability and scalability.

Skills

Distributed systems

Python

Go/Rust/C++

Performance engineering

LLM frameworks

GPU utilization

Kubernetes

Observability

Incidents handling

Education

Bachelor’s or Master’s in Computer Science or related field

Tools

vLLM

TensorRT-LLM

Kubernetes

Job description

Bright Vision Technologies is seeking a Model Serving Engineer to design, build, and operate high-performance inference platforms for serving large machine learning models in production. The role focuses on the systems engineering side of AI deployment, including request routing, batching, caching, autoscaling, GPU utilization, and end-to-end observability across diverse model workloads.

The ideal candidate brings strong distributed systems and performance engineering expertise, has shipped