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.
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.
Play a crucial role in managing and scaling our cloud-based systems. The ideal candidate will have a strong background in cloud infrastructure, automation, and continuous delivery. You will be responsible for ensuring the reliability, performance, and security of our cloud environments, with a particular focus on AWS .
As a Senior Infrastructure Engineer, you'll drive the technological advancement of our Infrastructure Platform within Raya. Leveraging best-in-class cloud technologies and container orchestration, your work will be central to delivering a reliable, secure, and scalable foundation that our product teams depend on daily. You can design infrastructure that maximizes application efficiency and resource utilization. You're enthusiastic about leveraging AI to enhance your own infrastructure workflows.
Easypost is seeking a highly experienced and skilled Senior Engineer to work with our DevOps team. This role will be involved in designing, building, and optimizing our cloud infrastructure, ensuring scalability, reliability, and high availability in a multi-Cloud environment. The ideal candidate will have deep expertise in cloud platforms and a strong background in DevOps and automation.
As a Senior Machine Learning Ops Engineer, you will design and build large-scale architectures, workflows, tools, and automation for processing data and apply machine learning engineering to solve global business challenges with a focus on making tasks easier for data scientists.
Use your experience to develop, maintain and implement Kubernetes clusters at scale that are ready for heavy/spiky ML workloads. Work closely with Data Science and Data Engineering teams to implement, optimize and scale workloads on Kubernetes using CI/CD, automation tools and scripting languages. Help Data Science and Data Engineering develop and implement specialized infrastructure to deliver tools/software to improve the reliability and scalability of services.