Remote MLOps Engineer: Scale AI Inference

Bright Vision Technologies; Sugar Land (TX); Remote; USD 100,000 - 150,000; Full time

Job summary

Bright Vision Technologies is seeking a highly skilled MLOps Engineer to design, build, and operate high-performance inference platforms for production ML systems. You will focus on systems engineering aspects of AI deployment, including routing, batching, caching, autoscaling, GPU utilization, and end-to-end observability across diverse model workloads.

The ideal candidate will have strong distributed systems experience, production-grade serving deployments, and the ability to balance latency,

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.

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 across model endpoints
• Build autoscaling and capacity management systems balancing 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
• Develop deployment workflows including canary releases, shadow testing, and automated rollback
• Operate incident response for high-availability AI services and drive durable reliability improvements
• Collaborate with ML and product teams to support new model releases and capability rollouts
• Implement security controls including request signing, content filtering, and abuse detection
• Document operational procedures, performance characteristics, and tuning guidance for internal teams
• Stay current with AI serving research and translate advances into production capabilities

Skills

Python

Go

Rust

C++

Distributed systems

Performance engineering

Incident response

Communication

Education

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

Tools

vLLM

TensorRT-LLM

Kubernetes

Job description

Bright Vision Technologies is seeking a highly skilled MLOps Engineer to design, build, and operate high-performance inference platforms for production ML systems. You will focus on systems engineering aspects of AI deployment, including routing, batching, caching, autoscaling, GPU utilization, and end-to-end observability across diverse model workloads.

The ideal candidate will have strong distributed systems experience, production-grade serving deployments, and the ability to balance latency,