MLOps Engineer

Bright Vision Technologies is hiring a fully remote MLOps Engineer to design, build, and operate high-performance inference platforms for large machine learning models in production. The role focuses on serving systems, GPU optimization, autoscaling, and observability for LLMs, vision models, and recommendation systems. This is a full-time W2 position for candidates with 6+ years of experience in distributed systems or ML infrastructure.

• Design and operate model serving platforms supporting 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.
• 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.
• Implement security controls and document operational procedures for high-availability AI services.