Remote ML Systems Engineer Scalable Inference Platforms

Bright Vision Technologies; Round Rock (TX); On-site; USD 145,000 - 165,000; Full time

Job summary

Bright Vision Technologies is seeking an ML Systems Engineer to design, build, and operate high-performance inference platforms for serving large ML models in production. The role emphasizes systems engineering for AI deployment, including routing, batching, caching, autoscaling, GPU utilization, and end-to-end observability across diverse workloads.

The ideal candidate will have strong distributed-systems and performance-engineering expertise, with experience shipping serving systems at scale

Qualifications

• Bachelor's or Master's degree in Computer Science or related field.
• Six+ years of experience in distributed systems, infrastructure, or ML platform engineering.
• Strong Python and systems language (Go, Rust, or C++) proficiency.
• Experience operating high-throughput, low-latency services in production.
• Hands-on experience with LLM/model inference frameworks (vLLM, TensorRT-LLM).
• Understanding of GPU architecture and accelerator utilization.
• Familiarity with Kubernetes, autoscaling, and cloud platforms.
• Observability stacks with metrics, tracing, and logging.
• Strong performance engineering and capacity planning.
• Excellent communication and incident response skills.

Responsibilities

• Design, build, and operate high-performance ML inference platforms for production ML models.
• Own request routing, batching, caching, autoscaling, and GPU utilization.
• Ensure end-to-end observability across diverse model workloads.
• Balance latency, throughput, cost, and quality in ML serving.
• Collaborate with teams to ship serving systems at scale.

Skills

Python

Go

Rust

C++

Distributed systems

ML serving frameworks

GPU utilization

Kubernetes

Observability

Performance engineering

Incident response

Education

Bachelor's or Master's in Computer Science

Tools

Kubernetes

TensorRT-LLM

vLLM

Job description

Bright Vision Technologies is seeking an ML Systems Engineer to design, build, and operate high-performance inference platforms for serving large ML models in production. The role emphasizes systems engineering for AI deployment, including routing, batching, caching, autoscaling, GPU utilization, and end-to-end observability across diverse workloads.

The ideal candidate will have strong distributed-systems and performance-engineering expertise, with experience shipping serving systems at scale