Machine Learning Infrastructure Engineer

Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. The Machine Learning Infrastructure Engineer will design, build, and operate reliable, high-performance inference platforms for production machine learning models, focusing on request routing, batching, caching, autoscaling, GPU utilization, and observability. The role also requires applying distributed systems and performance engineering expertise to balance latency, throughput, cost, and quality in ML serving.

Requirements:

• Bachelor's or Master's degree in Computer Science or a related field
• 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
• Strong understanding of GPU architecture, memory hierarchies, and accelerator utilization
• Familiarity with Kubernetes, autoscaling, and modern cloud platforms
• Experience with observability stacks including metrics, tracing, and structured logging
• Solid grounding in performance engineering and capacity planning
• Strong communication and incident response skills
• Open-source contributions to model serving infrastructure
• Experience with multi-region or globally distributed AI serving
• Familiarity with model quantization, distillation, and compression techniques
• Exposure to FinOps for AI workloads and cost-efficient serving design
• Experience supporting external-facing AI APIs at scale