Remote ML Systems Engineer: Scalable AI Inference

United States Digital Space LLC; United States; Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking an ML Systems Engineer to design, build, and operate high‑performance inference platforms for production ML models. The role focuses on systems engineering of AI deployment, including routing, batching, autoscaling, GPU utilization, and observability.

You will collaborate with ML and product teams to support new model releases, implement security controls, and drive reliability improvements.

Qualifications

• Six or more years of experience in distributed systems, infrastructure, or ML platform engineering.
• Strong proficiency in Python and a systems language such as Go, Rust, or C++.
• Deep experience operating high‑throughput, low‑latency services in production.
• Hands‑on experience with LLM or large model inference frameworks such as vLLM or TensorRT‑LLM.

Responsibilities

• Design and operate model serving platforms supporting diverse workloads including LLMs, vision models, and recommendation systems.
• Optimize inference performance using continuous batching, paged attention, speculative decoding, and request multiplexing.
• Implement multi‑tenant routing, rate limiting, and quality‑of‑service policies across model endpoints.
• Build autoscaling and capacity management systems that balance latency, throughput, and cost.
• Tune GPU utilization, memory management, and KV cache strategies for LLM serving workloads.
• Integrate model serving with API gateways, identity systems, and observability platforms.
• Implement caching, prompt deduplication, and response reuse strategies where appropriate.
• Drive end‑to‑end observability including latency histograms, queue dynamics, GPU utilization, and error tracking.

Skills

Distributed systems

Python

Go/Rust/C++

ML serving

Education

Bachelor’s or Master’s degree in Computer Science

Tools

Kubernetes

vLLM

TensorRT-LLM

Job description

Bright Vision Technologies is seeking an ML Systems Engineer to design, build, and operate high‑performance inference platforms for production ML models. The role focuses on systems engineering of AI deployment, including routing, batching, autoscaling, GPU utilization, and observability.

You will collaborate with ML and product teams to support new model releases, implement security controls, and drive reliability improvements.