Remote MLOps Engineer: Scalable AI Serving & Operations

Bright Vision Technologies; United States; Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking a seasoned MLOps Engineer to design, build, and operate high-performance inference platforms for production ML models. You will focus on systems engineering, request routing, batching, caching, autoscaling, and observability across diverse workloads.

The ideal candidate has strong distributed systems experience and has shipped serving systems at scale, balancing latency, throughput, cost, and quality in ML deployment.

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 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.
• Strong understanding of GPU architecture, memory hierarchies, and accelerator utilization.

Responsibilities

• Design and operate model serving platforms supporting diverse workloads including LLMs, vision models, and recommendation systems.
• Optimize inference performance using batching, paged attention, speculative decoding, and request multiplexing.
• Implement multi-tenant routing, rate limiting, and QoS policies across endpoints.
• Build autoscaling and capacity management systems balancing latency and cost.
• Tune GPU utilization, memory management, and KV cache strategies for LLM serving.
• Integrate model serving with API gateways, identity systems, and observability platforms.
• Implement caching, deduplication, and response reuse where appropriate.
• Drive end-to-end observability including latency histograms, queue dynamics, GPU utilization, and error tracking.
• Develop deployment workflows including canary releases, shadow testing, and automated rollback.
• Operate incident response for high-availability AI services and drive reliability improvements.
• Collaborate with ML and product teams to support new model releases.
• Implement security controls including request signing, content filtering, and abuse detection.
• Document operational procedures and tuning guidance for internal teams.
• Stay current with AI serving research and translate into production capabilities.

Skills

Python

Go

Rust

C++

Distributed systems

ML platform

Kubernetes

Observability

Performance engineering

Education

Bachelor's or Master's in Computer Science

Tools

TensorRT-LLM

vLLM

Kubernetes

Job description

Bright Vision Technologies is seeking a seasoned MLOps Engineer to design, build, and operate high-performance inference platforms for production ML models. You will focus on systems engineering, request routing, batching, caching, autoscaling, and observability across diverse workloads.

The ideal candidate has strong distributed systems experience and has shipped serving systems at scale, balancing latency, throughput, cost, and quality in ML deployment.