Top Remote Infrastructure Engineer Jobs

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.

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

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.

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.

The Software Engineer will manage data collection for AI model training, enhance the ingestion pipeline on GCP, and collaborate with the AI team to improve dataset quality and efficiency.

The role involves managing data collection for AI model training, extending cloud infrastructure, and collaborating with scientists to enhance data quality and scale.

The role involves data collection for model training, extending ingestion pipeline infrastructure, and collaborating on dataset roadmap execution.

Join the AI team at Speechify to develop data collection processes, enhance cloud infrastructure, and collaborate on data strategies for next-gen models.

As a Software Engineer focused on Data at Speechify, you'll manage data collection and ingestion for model training, enhance cloud infrastructure, and collaborate closely with AI scientists to optimize data quality and cost-efficiency for next-gen products.

The Software Engineer will manage data collection for AI model training, operate cloud infrastructure, and collaborate with the AI team to enhance data quality and scale.

The role involves data collection for AI model training, managing cloud infrastructure, and collaborating with scientists to enhance data quality and processing.

The role involves data collection for model training, managing and extending the cloud infrastructure on GCP, and collaborating with scientists to enhance data quality and scalability.

This role involves data collection for model training, operating cloud infrastructure, and collaborating with AI team members to enhance data quality and efficiency.

The Software Engineer will manage data collection for AI model training, operate cloud infrastructure, and work closely with scientists to enhance data quality and efficiency.

The Software Engineer will enhance data collection for AI model training, manage cloud infrastructure, and collaborate on dataset roadmap at Speechify.

The role involves data collection for model training, cloud infrastructure operation and extension, and collaborative roadmap crafting for datasets to enhance Speechify's products.

The role involves sourcing audio data, managing cloud infrastructure on GCP, and collaborating with the AI team to enhance data quality and processing for model training.

The Software Engineer will manage data collection for model training, improve cloud infrastructure on GCP, and collaborate with data scientists to enhance dataset quality and scale.

The role involves managing data collection and ingestion for AI model training, operating cloud infrastructure, and collaborating on dataset roadmap development.