CloudGeometry

Compensation

Full Description

Remote At CloudGeometry, we're redefining how modern data and AI systems are built. As a leading cloud-native engineering firm, we work with pioneering technology companies to deliver high-impact solutions across infrastructure, machine learning, and intelligent applications. We are looking for a highly skilled AI Infrastructure Engineers x 5 people to join our growing team supporting large-scale AI/ML systems. This is a hands-on engineering role focused on building scalable, secure, and production-ready infrastructure that powers ML workflows end-to-end—from experimentation to deployment and monitoring. What You’ll Do • Design, implement, and maintain robust infrastructure for ML workflows across real-time and batch environments. • Build and support production-grade model lifecycle systems, including registration, versioning, and deployment workflows. • Develop APIs and backend services in TypeScript and Python to support model integration and orchestration. • Manage and optimize infrastructure using AWS and infrastructure-as-code (CDK preferred). • Work with Databricks MLFlow for end-to-end model management, including asset bundling and serving pipelines. • Collaborate with cross-functional teams including ML scientists, backend engineers, and DevOps to deliver high-impact features. • Monitor and improve infrastructure reliability, security, and performance across diverse deployment targets. • Contribute to CI/CD workflows, container orchestration (Docker, ECS), and automation for ML pipelines. Why Join CloudGeometry? You’ll work alongside top-tier engineers across the US, LATAM, and Europe on cutting-edge projects in AI, cloud, and enterprise SaaS. We value deep technical curiosity, strong collaboration, and a bias for action in solving meaningful problems. • Seniority Level Mid-Senior level • Industry • Software Development • Employment Type Full-time • Job Functions • Engineering • Information Technology • Skills • Large Language Models (LLM) • Software as a Service (SaaS) • Databricks Products • Python (Programming Language) • Infrastructure • TypeScript • MLflow • MLOps • Amazon Web Services (AWS) Requirements What We’re Looking For • 7+ years in software or infrastructure engineering with proven experience supporting AI/ML systems. • Deep hands-on experience with AWS services and modern IaC practices (Terraform/CDK). • Strong backend programming skills in TypeScript and Python. • Production-level use of MLFlow for model management and deployment. • Expertise in containerization (Docker), CI/CD automation, and orchestration tools. • Solid understanding of designing scalable and secure systems in cloud-native environments. • Strong communication skills, able to bridge gaps between engineering and product stakeholders. • Comfortable in fast-paced, collaborative environments working across time zones. Nice to Have • Exposure to LLM infrastructure and frameworks (e.g., DSPy, LangChain). • Knowledge of LLM performance metrics: latency, cost monitoring, and usage optimization. • Familiarity with semantic search tools and vector stores (e.g., OpenSearch, Pinecone). Benefits • Remote anywhere • Coworking space financial coverage • Flexible working hours • B2B with multiple benefits • Paid days off annually • Workspace program: 2500$ for work equipment of your choice. • Paid courses and certifications: example AWS, CKA, ML certifications • Participation at international conferences: like CNCF Summits, Kubecon, others Submit Resume Send us an application to jobs@cloudgeometry.com, and we’ll contact you in shortly.