Senior Data Platform Engineer - Remote ML Inference & Ops

Bright Vision Technologies; Oregon; Hybrid; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies, a technology consulting and software development company, is seeking a Data Platform Engineer for a 100% remote US-based role. You will design, build, and operate high-performance inference platforms for serving large ML models in production, focusing on end-to-end observability and scalable systems.

The ideal candidate has deep distributed systems expertise, shipped serving systems at scale, and can balance latency, throughput, and cost while communicating clearly in

Qualifications

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

Skills

Distributed systems

Python

Go/Rust/C/C++

Kubernetes

Cloud platforms

Observability

LLM inference frameworks

GPU architectures

Performance engineering

Incident response

Education

Bachelor's or Master's in Computer Science

Tools

Kubernetes

TensorRT-LLM

vLLM

Job description

Bright Vision Technologies, a technology consulting and software development company, is seeking a Data Platform Engineer for a 100% remote US-based role. You will design, build, and operate high-performance inference platforms for serving large ML models in production, focusing on end-to-end observability and scalable systems.

The ideal candidate has deep distributed systems expertise, shipped serving systems at scale, and can balance latency, throughput, and cost while communicating clearly in