DevOps Engineer
Design, implement, and maintain cloud infrastructure and CI/CD pipelines. Collaborate with developers, SRE, and Security to ensure system reliability, scalability, and security.
Infrastructure Engineer responsible for securing, scaling, and maintaining cloud architecture, Kubernetes clusters, ML pipelines, and CI/CD systems at a computer vision AI startup. Must have production Kubernetes, IaC, and AWS/GCP experience.
As a member of our infrastructure team, you'll be at the heart of a fast-paced startup environment. Your primary focus will be on striking the right balance between rapid delivery, high reliability, and robust security. You'll act as an infrastructure engineer, developer, or security analyst as needed.
You will be securing, scaling, and maintaining the core infrastructure that powers our product. This includes our cloud architecture, databases, file storage, search clusters, microservices, and machine learning pipelines. You'll work closely with our product team and collaborate across the company on product, operations, and customer-facing projects.
Design, implement, and maintain cloud infrastructure and CI/CD pipelines. Collaborate with developers, SRE, and Security to ensure system reliability, scalability, and security.
Build automation and systems to provision and orchestrate GPU hardware into scalable Kubernetes clusters. Requires deep Linux expertise, provisioning experience, and strong programming in Python/Go.
Site Reliability Engineer builds and maintains scalable infrastructure for ML model deployment, automates CI/CD pipelines, and ensures reliability using tools like Kubernetes and Terraform. Collaborates cross-functionally, owns projects end-to-end, and mentors juniors; bachelor's in CS or related field required.
Builds internal tooling, monorepos, CI/CD pipelines, and shared libraries to boost engineering productivity. Requires strong proficiency in Go/Python, Kubernetes/Docker experience, and monorepo management.
Builds and maintains infrastructure components for ML inference platform using Python and Go. Implements Kubernetes deployments, monitoring systems, and resource management for efficient model serving, requiring Kubernetes knowledge and ML basics.