Remote Devops Jobs • Kubernetes

As a DevOps engineer you will maintain and enhance established AWS Cloud infrastructure while collaborating with our existing DevOps team. Take ownership of specific components to distribute workload across the team and develop comprehensive application understanding to improve infrastructure design, optimize deployment pipelines, and ensure SaaS environment reliability.

You will play a critical role in building and maintaining scalable infrastructure, managing CI/CD pipelines, and deploying cloud-native and bare-metal applications. This role requires a high level of technical expertise, a collaborative mindset, and a strong desire to continuously improve systems and processes

Observability Platforms is focused on creating visibility into DigitalOcean’s services and infrastructure by designing, building, and operating internal logging, metrics, distributed tracing, error reporting, monitoring, and alerting platforms that are depended on to ensure good, reliable experiences for DigitalOcean’s customers. The senior engineer will integrate and operate open source observability software and implement features to improve operability and next generations of metrics and logging.

Design and implement solutions to problems of scale for multi-site deployment and management of CoreWeave’s global server hardware fleet. Build and maintain backend services and APIs (gRPC/REST) in Go or Python to interact with Kubernetes and other infrastructure systems. Develop provisioning services, automation workflows, and fleet management tools that span from bare metal to container orchestration.

We are looking for a skilled and motivated Lead Infrastructure Engineer to lead our Platform Engineering team. As the team leader, you will direct the planning, design, development, and implementation of our platform architecture, ensuring it meets the needs of our growing product portfolio. You will guide a talented team of engineers, driving best practices and fostering a culture of excellence and innovation.

The Reliability Engineering team helps realize our vision by supporting Coinbase engineering teams to build software that is world-class in terms of its reliability. As a core service team, Coinbase Reliability Engineers work closely with the rest of engineering. Improve observability, reliability and availability by defining and measuring key metrics. Build automation and improve systems to eliminate toil and operations work.

Implementation and maintenance of scalable solutions following DevOps best practices in a leading Gaming industry company. Process automation using Terraform or AWS CloudFormation, enabling creation and management of AWS infrastructure and applications in an internal on-prem cluster. Building and maintaining CI/CD pipelines, automation of tests, deployments, and rollback strategies.

As a Platform engineer, MLOps, you will be critical to deploying and managing cutting-edge infrastructure crucial for AI/ML operations, and you will collaborate with AI/ML engineers and researchers to develop a robust CI/CD pipeline that supports safe and reproducible experiments. Your expertise will also extend to setting up and maintaining monitoring, logging, and alerting systems to oversee extensive training runs and client-facing APIs.

Be part of a dynamic team that is shaping the future of energy and technology. Build and maintain backend systems and data pipelines for AI-based software platforms, integrating SQL/NoSQL databases and collaborating with engineering teams to enhance performance. Design, deploy, and optimize cloud infrastructure on Google Cloud Platform, including Kubernetes clusters, virtual machines, and cost-effective scalable architecture.

As a Platform engineer, MLOps, you will be critical to deploying and managing cutting-edge infrastructure crucial for AI/ML operations, collaborating with AI/ML engineers and researchers to develop a robust CI/CD pipeline that supports safe and reproducible experiments. Your expertise will extend to setting up and maintaining monitoring, logging, and alerting systems to oversee extensive training runs and client-facing APIs. You will ensure that training environments are optimally available and efficiently managed across multiple clusters, enhancing our containerization and orchestration systems with advanced tools like Docker and Kubernetes.