ML Infrastructure Engineer

ML 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: ML Infrastructure Engineer Location: 100% Remote (U.S.) Position Type: Full-time, Direct W2 Salary Range: $100,000–$150,000 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 an AI Infrastructure Engineer to design, build, and operate the platform layer that powers large-scale AI training and inference workloads. The role focuses on GPU clusters, distributed training frameworks, scheduling, storage performance, and developer experience for ML engineers and researchers, with strong emphasis on reliability, efficiency, and cost control. The ideal candidate has built or operated production AI infrastructure at scale, understands the interaction between hardware, kernel, scheduler, and ML framework, and brings strong software engineering discipline to platform work. Key Responsibilities Design and operate GPU and accelerator infrastructure for training and inference, spanning on-prem clusters, cloud-managed services, and hybrid configurations. Build scheduling, queueing, and resource-sharing systems that maximize accelerator utilization across many teams. Integrate frameworks such as PyTorch, JAX, DeepSpeed, FSDP, Megatron-LM, and Ray Train into a unified platform offering. Operate high-performance storage systems and data pipelines that keep accelerators fed with training data at near-line-rate. Design networking architectures supporting RDMA, InfiniBand, NCCL, and high-bandwidth collective communication. Build observability for AI work