AI Infrastructure Engineer

AI 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: AI 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 configurationsBuild scheduling, queueing, and resource-sharing systems that maximize accelerator utilization across many teamsIntegrate frameworks such as PyTorch, JAX, DeepSpeed, FSDP, Megatron-LM, and Ray Train into a unified platform offeringOperate high-performance storage systems and data pipelines that keep accelerators fed with training data at near-line-rateDesign networking architectures supporting RDMA, InfiniBand, NCCL, and high-bandwidth collective communicationBuild observability for AI workloads including utilization, throughput, training stability, and failure-mode analyticsImplement checkpointing, restart, and fault-tolerance patterns for long-running training jobs at scaleDrive cost optimization across compute, storage, and networking through scheduling, spot capacity, and right-sizingDevelop developer tooling and paved-road workflows that let researchers launch experiments safely and efficientlyPartner with research and applied ML teams to plan capacity for upcoming training runsImplement security controls, isolation, and access management for multi-tenant AI infrastructureDrive automation across cluster provisioning, lifecycle management, and configuration enforcementMaintain runbooks, capacity dashboards, and operational documentation for the AI platformStay current with AI infrastructure research, accelerator hardware, and emerging open-source AI tooling Required Qualifications Bachelor’s or Master’s degree in Computer Science or a related fieldSix or more years of experience in infrastructure, platform, or HPC engineeringHands-on experience operating GPU clusters or large-scale ML training infrastructureStrong proficiency in Python and at least one systems language such as Go or C++Deep understanding of distributed training, accelerator architectures, and collective communicationExperience with Kubernetes, Slurm, Ray, or similar scheduling systems for ML workloadsStrong understanding of Linux internals, networking, and high-performance storageExperience with at least one major cloud provider’s ML infrastructure offeringsStrong software engineering practices including testing, CI/CD, and code reviewExcellent communication and cross-functional collaboration skills Preferred Qualifications Experience operating InfiniBand or RDMA networking at scaleContributions to open-source ML infrastructure projectsFamiliarity with custom orchestrators or research-grade training stacksExposure to frontier model training operationsExperience with FinOps for AI workloads How to Apply Would you like to know more about this opportunity? For immediate consideration, please send your resume to venkat.r@bvteck.com or contact us at (908) 505-3899. Learn more about Bright Vision Technologies at www.bvteck.com. Bright Vision Technologies is an Equal Opportunity Employer. Equal Employment Opportunity (EEO) Statement Bright Vision Technologies (BV Teck) is committed to equal employment opportunity (EEO) for all employees and applicants without regard to race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, veteran status, or any other protected status as defined by applicable federal, state, or local laws. This commitment extends to all aspects of employment, including recruitment, hiring, training, compensation, promotion, transfer, leaves of absence, termination, layoffs, and recall. BV Teck expressly prohibits any form of workplace harassment or discrimination. 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