Top Remote Infrastructure Engineer Jobs

Design and build scalable backend components and indexing pipelines for semantic and hybrid retrieval, build retrieval orchestration and knowledge-graph services, improve retrieval quality via evaluation and observability, design APIs, and optimize latency, throughput, cost, reliability, and security for large-scale AI inference and retrieval workloads.

The Infrastructure Software Engineer will design backend services, drive reliability, manage observability tools, and enhance deployment processes in a collaborative setting.

Responsible for overseeing physical infrastructure installation projects, ensuring quality control, managing contractors, and acting as a subject matter expert in fiber optics and structured cabling.

The Engineering Director will lead and manage the cloud infrastructure and developer enablement, focusing on AI-native systems, team development, and security operations.

Design and maintain production-grade cloud infrastructure for Tessera's AI systems, leveraging Terraform and Kubernetes across multiple cloud providers, while automating CI/CD pipelines and ensuring operational excellence.

Loti AI seeks a DevOps engineer for decentralized infrastructure to deploy, scale, and maintain distributed systems, manage IPFS clusters, and oversee blockchain nodes.

As a Software Engineer in ML Infrastructure, you will develop scalable data pipelines, enhance data discovery, and collaborate with teams on data organization and ML features.

Design and develop scalable, high-performance data and API infrastructure for real-time processing. Mentor engineers and collaborate with teams to enhance AI model evaluations.

The role involves designing and building data pipelines for analyzing user feedback on AI models, ensuring data quality and infrastructure scalability.

Develop and maintain components for machine learning inference platform. Focus on Kubernetes deployments, resource management, and performance monitoring.

The role involves managing full technical lifecycle of client cloud deployments, designing integrations, maintaining infrastructures, and engaging with clients directly.

Lead the optimization and performance analysis of distributed training and inference workloads on NVIDIA GPU platforms, with responsibilities including debugging, benchmarking, and ensuring reliability of large-scale AI systems.

The Senior Solutions Engineer will design and implement infrastructure for AI and HPC workloads, engage with customers, and lead technical discovery and architecture design.

The Software Engineer will manage data collection, optimize cloud infrastructure for data ingestion, and collaborate with AI researchers to enhance datasets for model training.

As a Senior Software Engineer on the Infrastructure team, you'll build and manage critical systems, contribute code, handle incidents, and enhance developer tooling.

Design, operate, and scale ML data and training pipelines for autonomous driving. Build distributed training, orchestration, CI/CD and infrastructure-as-code; maintain data/metadata stores and tooling to support large-scale model training and evaluation across cloud and cluster environments.

The Staff Software Engineer will lead technical strategy and execution in cloud infrastructure, design scalable systems, and enhance reliability across all engineering teams while mentoring other engineers.

Lead development and optimization of the compiler stack for ML systems, collaborate across teams, integrate and deploy products, map ML operations to hardware, and drive compiler infrastructure innovation and performance debugging.

Own reliability across vehicle and cloud stacks for AUV operations: onboard Jetson/ROS2 compute, topside systems, cloud ingestion/processing and customer platform. Build automation, observability, runbooks, and self-recovery to reduce on-call toil; manage AWS infrastructure, IaC, container orchestration, and reliability targets. Participate in shared 12-hour on-call shifts and field deployments, mentor team on operational excellence.

Design and operate large-scale GPU infrastructure for distributed AI training, ensuring reliability, performance, and efficient customer partnerships.

As a Software Engineer in AI Infrastructure, you will design and develop core platform components, build APIs and services, enhance performance, and automate tooling while collaborating across teams and improving system reliability.

The Site Reliability Engineer will provision and manage Kubernetes clusters, build automation tools, debug customer issues, and improve infrastructure reliability.

Lead platform reliability: define SLOs/error budgets, own observability and deploy pipelines, harden integrations with dental systems, operate LLM-driven workflows safely, build incident practices, and raise engineering reliability across the company.

Design, develop, and maintain high-performance distributed storage software and protocol APIs (file, block, object). Build scalable, resilient storage services, integrate with hardware (NVMe, GPU-direct), troubleshoot production data center issues, and participate in full SDLC for on-prem storage solutions.

Lead design and implementation of high-performance distributed storage systems across object, block, and file paradigms. Drive architecture, mentor engineers, integrate storage with networking/compute/DPUs, optimize protocol performance, troubleshoot production data center issues, build benchmarking and observability tooling, and collaborate on cross-functional AI infrastructure deployments.