HappyCo is looking for an experienced DevOps Manager to co-ordinate the development, management and maintenance of our cloud environments, ensuring they are scalable, efficient, and well-optimized for our engineering teams. This role involves overseeing system performance and uptime, refining monitoring processes, and enhancing incident response to reduce downtime.

As an SRE you will build and maintain systems, plan for capacity needs, respond to emergencies, enhance security measures, partner with internal and external compliance assessors, and collaborate with engineering stakeholders to resolve architectural bottlenecks and shape the future roadmap.

As a Staff SRE specializing in ML infrastructure, the primary responsibility is designing, developing, maintaining, and scaling the foundational infrastructure that enables Wikimedia's Machine Learning Engineers and Researchers to efficiently train, deploy, and monitor machine learning models in production.

The Platform Engineer will join the Veeam Data Cloud team to provide a secure, reliable, and easy-to-use platform. The mission is to enable the teams to build, test, deploy, and monitor the VDC product by writing and maintaining code to automate the public cloud infrastructure, software delivery pipeline, and other enablement tools.

Production Engineers keep Mysten's production infrastructure running smoothly even in the face of heavy traffic or attacks from adversaries, with expertise in release, deployment, logging, and monitoring processes. They have experience working with open-source frameworks and are obsessed with automation. They work closely with distributed systems experts.

As a Data Scientist Specialist focused on MLOPs your mission will be to own the design and deployment of scalable systems to train, monitor, and expose machine learning models in production. You will own the design of system architecture to train, retrain, develop, monitor, and expose machine learning models; Design, develop, and maintain scalable infrastructure for ML pipelines and APIs.

We are looking for a Senior Cloud Engineer, ML Platform to lead the next phase of scaling our cloud-based machine learning (ML) and computer vision (CV) systems. This role is instrumental in moving beyond batch processing and toward real-time, high-throughput ML infrastructure supporting multi-model systems.

As our first Machine Learning Engineer focusing on MLOps, you will play a pivotal role in operationalizing our ML models, ensuring they are scalable, reliable, and easy to monitor. You’ll work closely with our data scientists, server engineers, and infrastructure teams to build feature stores for model development and enhance model deployment.

As a Senior DevOps Engineer at Polygon Labs, you'll deploy, debug, tune and maintain large-scale Web deployments, high-performance, low-latency distributed applications, and container-based applications and microservices. You'll apply best practices for monitoring and observability, security and infrastructure automation to improve and expand the multi-cloud platform used by deployments.

As an SRE, you will take a Platform-first approach to solving problems, maintain our metrics environment, develop monitoring and alerting systems, respond to on-call duties, partner as a Subject Matter Expert, and collaborate with engineering stakeholders. You'll work closely with software development teams to resolve architectural bottlenecks and offer large-scale operational perspectives.