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 high-performance inference platforms for large machine learning models, focusing on the systems engineering aspects of AI deployment.

Responsibilities:

• Design, build, and operate high-performance, highly reliable inference platforms for serving large machine learning models in production
• Focus on the systems engineering side of AI deployment, including request routing, batching, caching, autoscaling, GPU utilization, and end-to-end observability across diverse model workloads

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