Backend Engineer
hace 4 semanas
This is a remote position. 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. 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. Requirements 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: $2,500 for work equipment of your choice. Paid courses and certifications (e.g., AWS, CKA, ML certifications) Participation at international conferences (e.g., CNCF Summits, KubeCon, others) Senior Level Mid‑Senior level Employment Type Full‑time Job Functions Engineering, Information Technology Industries Software Development Referrals increase your chances of interviewing at CloudGeometry by 2x. #J-18808-Ljbffr
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