Machine Learning Infrastructure Engineer

Machine Learning Infrastructure Engineer – Remote Bright Vision Technologies is a technology consulting and software development company delivering cloud, AI, data, and enterprise solutions across the United States. This is a fantastic opportunity to join an established and well-respected organization offering tremendous career growth potential. Job Title: Machine Learning Infrastructure Engineer Location: 100% Remote (U.S.) Position Type: Full-time, Direct W2 Salary Range: $105,000–$143,000 Annually Experience Required: 6+ years Sponsorship: U.S. Citizens, Green Card Holders, EAD Holders, and H-1B transfer candidates are encouraged to apply. We are unable to sponsor new H-1B visa petitions for this position. Job Summary We are seeking a Machine Learning Infrastructure Engineer to design, build, and operate high-performance, highly reliable inference platforms for serving large machine learning models in production. The role focuses 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. The ideal candidate brings strong distributed systems and performance engineering expertise, has shipped serving systems at scale, and understands the trade-offs between latency, throughput, cost, and quality in ML serving. Required Qualifications 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 stack